The Mendes Hershman Student Writing Contest is a highly regarded legal writing competition that encourages and rewards law students for their outstanding writing on business law topics. Papers are judged on research and analysis, choice of topic, writing style, originality, and contribution to the literature available on the topic. The distinguished former Business Law Section Chair Mendes Hershman (1974–1975) lends his name to this legacy. Read an edited version of this year’s third-place winning essay, submitted by Benjamin A. Glinton of Fordham University School of Law, Class of 2027.

Introduction: From Substitution Claims to Practice-Level Consequences

Few developments have generated more speculation about the legal profession’s future than the rapid advancement of generative artificial intelligence (“AI”). Since large language model (“LLM”) tools became publicly available in late 2022, commentators and legal industry observers have debated with increasing urgency whether AI will replace lawyers. Headlines have declared that AI can pass the bar exam, draft contracts indistinguishable from those produced by experienced attorneys, and complete in minutes due diligence reviews that previously required weeks of associate labor.^[1] This discourse is not without foundation, but framing the debate around replacement is analytically unhelpful. It blurs the more consequential question: not whether AI will replace lawyers, but how AI is already reshaping the structure of legal work and what follows from that transformation.^[2]

This paper addresses that question directly, focusing on transactional legal practice (mergers and acquisitions (“M&A”), private equity, capital markets, and corporate advisory) work that constitutes the core revenue engine of large law firms.^[3] Transactional practice is a particularly useful lens because it combines two categories of work that map cleanly onto AI’s strengths and limitations: document-intensive execution tasks on one hand, and judgment-intensive advisory functions on the other.^[4] AI is genuinely transforming the first category. It is structurally limited in the second. Understanding the boundary between them, and what it means for how legal work is organized, priced, and practiced, is the central analytical task this paper undertakes.

This paper’s thesis proceeds in two related parts. First, AI materially improves efficiency in document-intensive transactional workflows by enabling faster and more consistent performance of pattern-recognition tasks such as contract review, due diligence, precedent mining, and first-pass drafting.^[5] Second, the probabilistic architecture of generative AI systems creates durable structural constraints that currently prevent reliable performance on tasks that define legal judgment: reasoning about novel issues, making normative trade-offs between competing legal and policy values, and navigating the social and political context embedded in complex dealmaking.^[6] Because these limitations correspond directly to the core functions of corporate lawyering, AI does not eliminate the need for lawyers but instead reconfigures where legal judgment is exercised and where professional risk resides.^[7]

The “AI replacing lawyers” narrative fails because legal practice is not a single, undifferentiated activity. It is a composite of tasks with different cognitive profiles; some are highly susceptible to automation, and some are structurally resistant to it.^[8] Asking whether AI will replace lawyers is, therefore, like asking whether spreadsheets replaced accountants: the question misses the point.^[9] The more useful questions are which parts of legal work AI is changing, how those changes are propagating through the organization and economics of law firms, and what new demands they place on the lawyers who remain.

This paper follows in seven parts. Section II maps current AI deployment in transactional practice. Section III analyzes the structural limits of AI in legal judgment. Section IV examines real-world consequences inside BigLaw and corporate legal departments. Section V applies the paper’s framework to risk allocation in M&A transactions. Section VI analyzes the professional responsibility framework governing AI use. Section VII examines the long-term structural consequences of AI adoption for BigLaw as an industry. Section VIII details the trajectory of AI toward more effective normative legal reasoning. Together, these sections develop a coherent account of AI as a force that reshapes legal practice from within, concentrating professional judgment more precisely where it genuinely matters.

How AI Is Actually Used in Transactional Practice

Understanding AI’s long-term consequences for the legal profession requires starting from a precise empirical baseline: what AI is actually doing inside law firms and corporate legal departments today. The popular discourse shifts between utopian predictions of full automation and dismissive claims that legal work is too nuanced for machines; neither framing is useful. AI is being deployed in transactional practice in a defined set of high-volume, pattern-intensive workflows where its comparative advantages are clear, while human lawyers retain responsibility for the judgment-intensive work that gives transactions their legal and commercial significance.

Due Diligence and Document Review

The most widespread application of AI in transactional practice is due diligence, the process by which a buyer’s legal team reviews the target company’s contracts, corporate records, and regulatory filings to assess legal risk before closing. In large transactions, due diligence can involve tens of thousands of documents across multiple data rooms, historically consuming enormous amounts of junior associate time while creating significant opportunities for human error due to fatigue and inconsistency.^[10]

AI-powered contract review platforms can now classify documents by type; extract specific contractual provisions; identify clauses with particular legal significance (change-of-control triggers, assignment restrictions, and termination rights); and flag deviations from market-standard terms—all at speeds far exceeding human reviewers.^[11] Platforms such as Kira Systems, Luminance, and Relativity have become standard infrastructure at many large firms precisely because they operationalize AI’s core comparative advantage: pattern recognition across large datasets.^[12] Where a human reviewer must read each contract sequentially, an AI system can simultaneously process hundreds of agreements, extract the same provision across all of them with consistent accuracy, and present results in a structured format for attorney review.

Independent studies have found that machine-learning-assisted review achieves accuracy rates comparable to, and in some conditions exceeding, those of experienced human reviewers conducting exhaustive manual review.^[13] This performance profile makes AI-assisted due diligence not merely faster but qualitatively superior in consistency, reducing the variance that results when large document sets are distributed across multiple junior reviewers working under time pressure.

The practical implications for deal execution are significant. Due diligence timelines that previously stretched across several weeks can now be compressed substantially, enabling faster transaction closings and reducing the labor costs associated with large-scale review. Critically, however, AI-assisted due diligence does not eliminate the need for attorney judgment; it redirects it. The AI surfaces issues; the lawyer must assess their materiality, understand their transactional context, and determine the appropriate response. The analytical work of evaluating what a flagged clause means for the deal remains squarely within the domain of human professional responsibility.

Contract Analytics and Negotiation Support

Beyond initial due diligence, AI is increasingly deployed in ongoing contract analytics: systematic analysis of a firm’s or client’s existing contract portfolio to identify risk concentrations, track negotiation outcomes, and benchmark terms against market standards.^[14] In M&A practice, this function supports both the diligence process and post-closing integration work, in which acquirers must assess how target-company contracts interact with their existing agreements.

Contract analytics platforms enable legal teams to answer questions that would previously have required substantial manual effort: How many of the target’s customer contracts contain most-favored-nation pricing provisions? What percentage includes automatic renewal clauses that could complicate post-closing restructuring? Are there patterns in how certain counterparties have historically negotiated indemnification caps? AI makes these analyses tractable at scale, surfacing information that informs negotiation strategy and risk assessment in ways that were practically unavailable before.

The negotiation support function of AI is more limited but growing. Some platforms now offer clause-level benchmarking against negotiated market precedents, allowing attorneys to assess whether a proposed contractual provision is favorable, unfavorable, or within the range of typical outcomes for comparable transactions.^[15] This capability enhances the informational foundation for negotiation, though the strategic decisions it informs remain with counsel.

Generative Drafting and Document Production

The application of generative AI to legal drafting represents a qualitatively different, and more contested, deployment than document review or analytics. LLMs can produce first-draft contract provisions, memoranda, term sheets, and other transactional documents from natural language prompts, drawing on patterns learned from the legal texts in their training data.^[16] Law firms including Allen & Overy, Latham & Watkins, and Davis Polk have disclosed pilots or deployments of generative AI drafting tools, and legal technology vendors have introduced purpose-built drafting platforms tailored to transactional practice.^[17]

The efficiency gains from AI-assisted drafting can be substantial for routine document production. A first draft of a standard nondisclosure agreement, board consent, or officer’s certificate that might previously have required an hour of junior associate time can be generated in seconds, freeing attorney time for review and customization rather than initial composition. For more complex instruments such as credit agreements, merger agreements, and purchase price adjustment mechanisms, AI can produce structurally coherent drafts that serve as useful starting points, though they require careful attorney review and substantial modification.

The critical limitation of generative drafting is that speed in producing text does not equate to accuracy in legal meaning. LLMs generate text by predicting statistically likely sequences of words based on training data; they do not reason about whether the provisions they generate are legally effective, commercially appropriate, or internally consistent in the context of a specific transaction.^[18] Attorneys who use AI-generated drafts without rigorous review risk incorporating provisions that are superficially plausible but legally deficient—a risk that courts and bar authorities are beginning to address directly. The well-publicized cases in which attorneys submitted AI-generated briefs containing fabricated citations illustrate the professional responsibility stakes of overreliance on generative tools.^[19]

The Structural Limits of AI in Legal Judgment

Mapping AI’s capabilities in transactional practice reveals a pattern: AI performs consistently well on tasks that can be decomposed into pattern recognition over well-defined inputs, and it performs unreliably on tasks that require genuine legal judgment. This is not a limitation that incremental scaling of existing architectures will straightforwardly overcome; it is a durable feature of how current probabilistic systems work, though one whose boundary may shift as architectures evolve. Understanding why this boundary exists is essential to understanding its implications for the practice of law.

The Architecture of Probabilistic Systems

LLMs generate outputs by predicting statistically likely continuations of input text based on patterns learned from training data.^[20] This architecture is highly effective for tasks where the correct output is, in fact, the statistically likely one—identifying the type of clause that typically follows the phrase representations and warranties of the seller, for example, or recognizing that a given provision deviates from market-standard language. It is structurally problematic for tasks that require reasoning beyond pattern frequency.

This characterization, while technically accurate, requires qualification.^[21] Current frontier models exhibit emergent capabilities that substantially exceed simple next-token prediction.^[22] Chain-of-thought reasoning enables models to decompose complex legal problems into intermediate analytical steps before reaching conclusions, producing outputs that reflect structured analysis rather than mere pattern completion.^[23] In-context learning allows models to absorb particularized information within a single interaction (a client’s risk profile, a set of deal terms, a jurisdictional preference) and adapt their outputs accordingly.^[24] Analogical transfer enables the application of reasoning patterns from one legal domain to structurally similar problems in another, a capacity that closely mirrors one of the core cognitive operations of legal practice.^[25] These capabilities are genuine and commercially significant; they account for the efficiency gains that AI-assisted legal work is already producing across transactional practice, and any framework that does not account for them will fail to describe the technology that lawyers are actually using.^[26]

The structural limitation, however, persists. Understanding why requires distinguishing between the sophistication of the output and the nature of the process that produces it.^[27] When a frontier model works through a material adverse change (“MAC”) clause analysis using chain-of-thought reasoning, it generates text that resembles the intermediate steps a human reasoner would produce because that is what structured legal reasoning looks like in the model’s training data.^[28] The model is constructing a reasoning trace, rather than maintaining an internal representation of the commercial reality it is analyzing.^[29] This distinction matters because these emergent capabilities are most reliable precisely where the training distribution is richest: standard contractual provisions, well-established regulatory frameworks, and frequently negotiated deal terms.^[30] They degrade in the conditions where legal judgment is most valuable: when the problem is genuinely novel, when the answer cannot be derived from the distribution of prior outcomes, and when the stakes require an accountable professional who can defend the reasoning behind a decision.^[31] Moreover, the gap between human few-shot generalization (the capacity to reason reliably from a small number of examples about genuinely unprecedented problems) and LLM in-context learning is not obviously closable through incremental architectural improvement alone.^[32]

Legal judgment regularly involves reasoning about situations for which there is no adequate historical precedent; making normative choices between competing legal values when text and precedent underdetermine the outcome; and applying professional experience to assess the credibility, motives, and likely behavior of counterparties in ways that cannot be reduced to textual pattern matching.^[33] These are not marginal or exotic features of legal work—they are at its core. The transactional lawyer’s value to clients lies precisely in the ability to navigate situations where the answer is not already encoded in existing patterns because if it were, sophisticated clients could find it themselves.

Novelty and the Limits of Training Data

One structural limitation of AI in legal practice is its dependence on training data that necessarily reflects past legal practice. An LLM trained on existing contracts, cases, and legal memoranda learns the patterns of how legal issues have been analyzed and resolved historically. It cannot reason reliably about genuinely novel legal questions—new regulatory regimes, unprecedented transaction structures, or emerging markets where established legal frameworks do not clearly apply—because it has no training signal for such situations.^[34]

This limitation is acutely consequential in transactional practice, where deal structures regularly test the boundaries of existing legal frameworks. The emergence of cryptocurrency-denominated acquisition consideration, the development of new regulatory approval requirements in merger control law, and the ongoing evolution of Delaware corporate law doctrine all present issues where the answer is not derivable from prior patterns. The lawyer who can reason from first principles about how established doctrine should apply to new circumstances provides value that AI systems structurally cannot replicate.^[35]

Normative Reasoning and Value Trade-Offs

Legal judgment also requires normative reasoning—the capacity to make principled choices between competing legal and policy values when text and precedent leave the outcome genuinely open.^[36] In transactional practice, these trade-offs are pervasive: How should an indemnification cap be set when litigation risk is uncertain? How aggressive should a contract interpretation be when it would benefit the client but expose the counterparty to unexpected liability? What level of disclosure is appropriate when regulatory requirements are ambiguous?

These questions do not have statistically predictable answers. They require the application of professional judgment informed by an understanding of legal doctrine, business context, client risk tolerance, and professional ethics. AI systems can surface relevant precedents and identify the range of market outcomes for comparable provisions, but they cannot make the normative judgment about which outcome is appropriate for a specific client in a specific transaction.^[37] That judgment is irreducibly human. The reason is that legal judgment is a normative act, requiring an accountable professional capable of being held responsible for its consequences.

This position is not without challengers, and the objection deserves serious engagement. A sophisticated critic might argue that normative judgment is itself reducible to patterns—that what lawyers call “value trade-offs” are, at a sufficiently granular level of analysis, structured preferences that can be learned from observed human decisions. Under this view, if a model trains on enough judicial opinions, regulatory guidance, negotiated deal terms, and legislative history, it might not merely describe what norms have been applied but replicate their application with sufficient fidelity to constitute functional normative reasoning. The argument gains traction from the demonstrated ability of LLMs to produce outputs that, on their face, closely resemble reasoned legal analysis—outputs that courts, practitioners, and scholars sometimes struggle to distinguish from human work product.^[38]

This objection should not be dismissed. But it conflates mimicry with judgment. The distinction matters because normative legal reasoning is not merely pattern reproduction—it is the capacity to make a defensible choice between competing values in a context where the choice has consequences for real parties and where the reasoning behind it can be interrogated, revised, and held accountable. When a lawyer advises a client on whether a particular contractual allocation of risk is commercially reasonable, the answer is not derivable from prior examples alone. It requires a judgment about what the client’s interests actually are, what the counterparty’s tolerance for risk exposure is likely to be, what a court in a particular jurisdiction would likely find reasonable, and whether the deal’s commercial logic supports deviation from market standard. Each of these inputs is contextually specific, and the decision that integrates them involves a form of practical legal reasoning that is irreducibly first-person: the lawyer is deciding what should be done in this one, drawing on prior outcomes without being determined by them.^[39]

There is also a deeper structural problem. AI systems are trained on outputs—on the artifacts of human judgment—but not on the deliberative process that produced them. They learn what decisions were made, not how the competing considerations were actually weighed, what was rejected, or why the result was regarded as justified. When a model reproduces the form of normative reasoning, it is reconstructing the surface of a decision-making process whose internal logic it has never observed. This is not a limitation that improved training data straightforwardly resolves; it reflects the fact that the normative dimension of legal judgment is embedded in a practice—a socially accountable form of reasoning—rather than in a dataset.^[40] Accordingly, even a well-calibrated model that consistently produces plausible normative outputs should be understood as approximating the products of legal judgment, not exercising it.

Social, Political, and Relational Context

Complex transactions are not purely legal events—they are social and political processes in which relationships, reputations, personalities, and power dynamics shape outcomes in ways that legal text does not capture.^[41] The decision to push hard for a particular contractual concession involves assessing the counterparty’s risk tolerance, the transaction’s strategic importance to both parties, the relationship between the principals, and the likely reaction of the other side’s counsel. These assessments require the kind of situated judgment that comes from professional experience and social intelligence.

AI systems have no genuine access to this social and relational context. They can process text; they cannot read a room, assess the credibility of a counterparty’s walk-away threat, or calibrate advice to the political dynamics of a corporate board. These capacities are central to what senior transactional lawyers actually do and are structurally unavailable to probabilistic systems operating on text inputs.^[42]

Practice-Level Consequences Inside BigLaw and Corporate Legal Departments

The deployment of AI in transactional practice is not merely a technology story—it is producing concrete, measurable changes in how law firms are organized, how legal work is priced, how risk is allocated between firms and clients, and how lawyers are trained. These consequences are already visible inside the industry and will accelerate as AI capabilities continue to develop.

Workflow Transformation and Staffing Implications

The most immediate organizational consequence of AI deployment is the compression of workflows that previously required large teams of junior associates. When AI can perform a first-pass review of ten thousand contracts in hours rather than weeks, the staffing calculus for large transactions changes fundamentally. Firms that have deployed AI-assisted due diligence tools report significant reductions in the associate hours required for document review, with some indicating reductions of 50 percent or more on review-intensive matters.^[43]

This compression has implications for staffing at every level. The junior associate pipeline, historically the entry point into BigLaw and the training ground for developing core analytical skills, is under structural pressure. If AI performs the document review work that previously occupied first- and second-year associates, the number of associates needed for that work decreases, and the developmental pathway through which associates built foundational skills is disrupted.^[44] The long-term implication is that firms will need to redesign associate development programs to substitute structured training for the incidental learning that previously occurred through high-volume document review.

Billing Models and Client Expectations

AI-driven efficiency creates direct tension with the billable-hour model that dominates BigLaw economics. When AI reduces the time required to complete a task, hourly billing produces lower revenue per matter unless rates are increased proportionally—a dynamic that sophisticated clients are already exploiting. Large institutional clients are increasingly demanding that efficiency gains from AI be passed through in the form of lower fees, either through reduced hourly billing or through alternative fee arrangements that price matters based on value rather than time.^[45]

This pressure is reshaping the competitive landscape. Clients who are well-informed about AI capabilities are asking firms to justify staffing decisions and to account for AI use in billing. Some clients have begun requiring firms to disclose when AI tools are used on their matters and to explain how efficiency gains are being shared. The long-term trajectory is toward value-based pricing models in which the price of legal services reflects the complexity and risk of the judgment involved rather than the volume of hours spent, with AI-assisted tasks priced at rates that reflect their reduced labor input.^[46]

Malpractice Risk and Quality Control

AI deployment creates new vectors of malpractice risk with which the profession is only beginning to grapple. The risks are less likely to involve overly wrong outputs, which experienced attorneys will catch, than subtly wrong ones: AI provisions that are legally plausible but commercially inappropriate, analyses that are accurate with respect to historical precedents but miss recently decided cases, or drafting that is internally consistent but fails to achieve the client’s actual objective.^[47]

The supervisory challenge is compounded by the speed and volume at which AI operates. When AI reviews thousands of contracts and produces a summary report, the reviewing attorney is, as a practical matter, trusting the AI’s extraction and classification decisions for the vast majority of documents, with detailed human review reserved for flagged items. The quality of that process depends entirely on the sophistication of the attorney’s understanding of the AI’s capabilities and limitations, and on the robustness of the quality control protocols the firm has established.^[48]

The harder malpractice question—and the one the profession has not yet adequately confronted—arises not when AI produces overtly fabricated outputs, but when it generates provisions that are subtly defective in ways that a competent attorney exercising reasonable care might not detect. Consider a scenario in which an AI system drafts a MAC clause for an acquisition agreement, the supervising attorney reviews the clause with appropriate diligence and approves it, and the provision later fails in litigation because of an interaction between the AI-generated carve-out language and a jurisdiction-specific interpretive doctrine that the attorney did not identify and that the AI’s training data did not adequately represent. In this scenario, the attorney has arguably satisfied the supervisory obligations established by Model Rules 5.1 and 5.3 and the competence standard of Rule 1.1—the review was conducted, the provision appeared legally sound, and the error was not reasonably detectable through the exercise of ordinary professional care. Yet the client has suffered a material loss attributable to a defect in the AI-generated work product. Where malpractice liability falls in such cases—whether with the supervising attorney, the firm, the AI vendor, or some allocation among them—is a question that existing professional responsibility frameworks are not well equipped to answer, and one that will become increasingly pressing as AI-generated provisions become more prevalent in executed agreements.

Disrupted Training Pipelines

The compression of junior associate work raises a structural challenge for the profession that extends beyond near-term staffing concerns. The traditional BigLaw training model relied on large volumes of supervised work—document review, due diligence, drafting under supervision—as the mechanism through which associates developed legal judgment over time.^[49] The incidental learning embedded in that work—understanding how contracts are structured, how provisions interact, how deal teams function under pressure—is difficult to replicate in the abstract.

If AI performs an increasing share of this foundational work, firms face the challenge of developing senior lawyers who have sufficient foundational knowledge to supervise AI effectively, exercise independent judgment, and advise clients in complex situations, even though they have not acquired that knowledge through the traditional developmental pathway.^[50] The profession has not yet developed consensus models for addressing this challenge, though some firms are experimenting with structured training programs, simulation-based learning, and deliberate mentorship frameworks designed to substitute for the experiential learning that automation is displacing.

Case Study: Risk Allocation in M&A Transactions

The theoretical framework developed in Sections III and IV finds concrete illustration in the design of risk-allocation mechanisms in M&A—a domain where AI’s capabilities and limitations are both acutely visible and commercially consequential.

The Structure of M&A Risk Allocation

The fundamental legal work of a corporate acquisition involves allocating risk between buyer and seller across multiple dimensions: the risk that the target’s business performs worse than represented, the risk that undisclosed liabilities emerge after closing, the risk that regulatory approvals are not obtained, and the risk of litigation arising from the transaction itself.^[51] This allocation is achieved primarily through three contractual mechanisms: representations and warranties, indemnification provisions, and MAC clauses—each of which requires layers of legal judgment that cannot be automated away.

AI’s Contribution to Risk-Allocation Work

AI can contribute meaningfully to the information-gathering and preliminary drafting phases of risk-allocation design. In diligence, AI can systematically extract representations and warranties from the target’s existing contracts, identify inconsistencies between those representations and the acquisition agreement’s representations, and flag provisions in third-party contracts that could be triggered by the transaction.^[52] In drafting, AI can generate first-pass provisions that incorporate standard market terms and identify the range of negotiated outcomes in comparable transactions.

The Irreducible Judgment in MAC Clauses

The limitations of AI become most visible in the design of MAC clauses—provisions that determine whether a buyer can terminate an acquisition agreement if the target suffers a material adverse change between signing and closing. The legal definition of what constitutes a “material adverse change” is among the most contested and fact-specific questions in Delaware corporate law, with judicial outcomes turning on nuanced assessments of business context, industry conditions, and the parties’ reasonable expectations at signing.^[53]

Designing an effective MAC clause for a specific transaction requires the attorney to make a series of normative judgments: How much downside risk should the buyer bear for industry-wide disruptions? How should the clause address known risks that are disclosed at signing but have uncertain magnitude? What carve-outs are appropriate given the target’s specific business and the competitive dynamics of the deal? These judgments cannot be derived from historical patterns because they depend on the parties’ risk tolerances, the strategic importance of the transaction, and the attorney’s assessment of how a Delaware court would evaluate the clause in future litigation.^[54]

An AI system can identify how MAC clauses have been structured in comparable transactions and what judicial decisions have said about specific formulations. However, it cannot make the normative judgment about which formulation is right for this client in this deal—and the consequences of getting that judgment wrong can be measured in billions of dollars.

Purchase Price Adjustment Mechanisms and Earn-Outs

Similar dynamics appear in the design of purchase price adjustment mechanisms and earn-out provisions. AI can assist with the mechanical aspects of drafting: generating accounting methodology definitions, structuring the calculation waterfall, and identifying market precedents for comparable provisions.^[55] But the design judgment—how to balance the buyer’s interest in protecting against deterioration with the seller’s interest in clean certainty, or how to structure an earn-out that incentivizes management without creating perverse incentives or litigation risk—requires the kind of experience-based professional judgment that is irreducibly human.

The practical significance of this framework for M&A practice is that AI enables the legal team to work from a richer informational foundation and to produce higher-quality first drafts more efficiently, while the judgment required to customize those drafts to the specific transaction remains the exclusive province of experienced counsel. The result is not that AI replaces the M&A attorney but that it raises the minimum informational baseline from which the attorney’s judgment operates.

Professional Responsibility Framework

The integration of AI into legal practice does not occur in a regulatory vacuum. Lawyers are subject to professional responsibility obligations that govern how technology can be used in the delivery of legal services, and the emergence of AI has begun to generate specific guidance—from bar associations, courts, and legal ethics authorities—about how those obligations apply.

Competence and the Duty to Understand AI Tools

Model Rule 1.1 requires that lawyers provide competent representation, including the “legal knowledge, skill, thoroughness and preparation reasonably necessary for the representation.”^[56] Comment 8 to Rule 1.1 extends this obligation to technology, providing that competent representation requires lawyers to keep abreast of “changes in the law and its practice, including the benefits and risks associated with relevant technology.”^[57]

Applied to AI, the competence obligation requires that attorneys who use AI tools in client representations understand those tools’ capabilities and limitations sufficiently to evaluate their outputs and identify their errors. This is a higher bar than simply knowing how to operate the tool—it requires understanding the architecture of probabilistic systems well enough to recognize the categories of error they are prone to produce, the types of tasks for which they are reliable, and the circumstances that require independent verification of AI-generated work.^[58]

The ABA’s Formal Opinion 512 (2024) addresses AI use directly, confirming that the competence obligation applies to AI tools and that lawyers must exercise independent judgment in reviewing AI-generated work product.^[59] The opinion specifically cautions against overreliance on AI outputs in contexts where independent verification is feasible, noting that the failure to review AI-generated work with appropriate care can constitute a breach of the competence obligation regardless of whether the AI-generated output ultimately proves accurate.

Supervisory Obligations and Delegation to AI

Model Rules 5.1 and 5.3 establish supervisory obligations for partners and supervising attorneys with respect to other lawyers and nonlawyer assistants, respectively.^[60] These rules have been interpreted to extend to AI tools when those tools are used to perform functions that would otherwise be performed by junior lawyers or legal assistants. The supervisory obligation requires that the supervising attorney establish adequate protocols for reviewing AI-generated work, maintain meaningful oversight of AI-assisted workflows, and take responsibility for the accuracy and quality of AI-generated outputs included in client deliverables.

This framework has important practical implications. A partner who delegates due diligence to an AI platform and accepts its output without adequate review is not insulated from professional responsibility liability by the delegation itself—the obligation to supervise the work, and the responsibility for its quality, remains with the supervising attorney.^[61] Firms are therefore required to develop institutional protocols for AI oversight, including quality control procedures, documentation requirements, and clear allocation of supervisory responsibility for AI-assisted workflows.

Confidentiality and Data Security Obligations

Rule 1.6’s confidentiality obligation creates significant compliance challenges for AI use, particularly when legal work involves the use of third-party AI platforms that process client documents on external servers.^[62] Uploading a client’s confidential contracts to an AI platform without adequate consent or data security protections can constitute a breach of confidentiality, regardless of whether the information is actually disclosed to unauthorized parties.

Firms have responded to this challenge by negotiating enterprise agreements with AI vendors that include data isolation provisions, prohibit use of client data for model training, and establish contractual liability for data breaches. The adequacy of these protections is a matter of ongoing legal and technical debate, and the professional responsibility requirements in this area are still developing.^[63] What is clear is that confidentiality compliance must be integrated into AI deployment decisions from the outset, not treated as an afterthought to technical implementation.

Candor to Tribunals and the Fabrication Problem

The widely publicized cases in which attorneys submitted AI-generated briefs containing fabricated case citations have brought Rule 3.3’s candor obligation into sharp focus.^[64] LLMs are prone to producing plausible-sounding but factually false citations—a phenomenon known as “hallucination”—because their architecture optimizes for statistical plausibility rather than factual accuracy. An attorney who submits AI-generated work product to a court without verifying citations and legal authority violates the candor obligation and exposes the client, the firm, and the attorney to sanctions.

While the hallucination problem is most evident in litigation contexts, it also has transactional relevance. AI-generated deal documents that cite regulatory provisions inaccurately, mischaracterize case law on MAC clauses, or misdescribe statutory requirements create risks beyond bar discipline—risks include potential malpractice liability and deal-level consequences if defective provisions are included in executed agreements.

Long-Term Structural Consequences for BigLaw

The cumulative effect of AI integration in transactional practice will, over time, produce structural changes in the BigLaw market that extend well beyond individual workflow modifications. These changes will affect the competitive dynamics of the legal industry, the economic model of large law firms, and the professional stratification of the lawyer workforce.

Market Consolidation and Competitive Differentiation

AI adoption is likely to accelerate market consolidation among large law firms, for reasons that reflect the economics of technology investment. Developing and deploying enterprise AI systems requires substantial capital investment in platform licenses, data infrastructure, training, and quality control systems.^[65] Firms with larger revenue bases can absorb these investments more easily and capture efficiency gains at scale, thereby creating a competitive advantage over smaller firms that cannot match their technology investments.

The competitive implications cut in multiple directions. On the one hand, AI enables large firms to serve clients at a lower cost per transaction, making them more competitive on price-sensitive matters. On the other hand, AI makes sophisticated legal capabilities more accessible to smaller firms and alternative legal service providers, potentially enabling competition with BigLaw in categories of work that previously required large-firm scale. The net effect is likely to be increased polarization: very large firms with substantial AI capability will compete for complex, judgment-intensive work at the high end of the market, while AI-enabled alternative providers capture routine work at the bottom, squeezing mid-market firms that cannot differentiate effectively on either dimension.^[66]

Business Model Disruption and the Billable Hour

The structural tension between AI-driven efficiency and hourly billing is more than a negotiating dynamic between firms and clients; it is a fundamental threat to the revenue model on which BigLaw has operated for decades.^[67] When AI dramatically reduces the time required to perform legal work, the billable hour either produces dramatically lower revenue or requires dramatic rate increases to maintain revenue levels. Neither outcome is sustainable in the long term in a competitive market where sophisticated clients can observe and challenge billing practices.

The likely resolution is an accelerated transition toward alternative fee arrangements—fixed fees, success fees, subscription models, and value-based pricing—that decouple legal service pricing from time input.^[68] This transition rewards firms that perform work efficiently and accurately, rather than those that generate high volumes of billable hours. In the long run, it favors AI-enabled practices that deliver judgment efficiently over labor-intensive practices that derive revenue from volume. The firms best positioned for this transition are those that can articulate and price the value of the judgment they provide, rather than depending on the volume of hours they bill.

Professional Stratification and the Reconfiguration of the Associate Model

The most consequential long-term structural effect of AI adoption may be the reconfiguration of the associate workforce and the professional hierarchy within large law firms. The traditional BigLaw pyramid, in which large classes of junior associates performing high-volume work supported smaller classes of senior associates and partners, depended on economics that are no longer stable when AI performs much of the foundational document work.^[69]

The emerging model is more stratified. At the top, senior lawyers with sophisticated judgment capabilities and client relationships will remain central—their work is the least susceptible to automation and the most valuable to clients. At the bottom, a smaller number of junior lawyers will handle AI-assisted work that still requires attorney oversight; but the volume of this work, relative to the number of people needed to do it, will be lower than in the past. In the middle, there is genuine uncertainty about what the mid-career lawyer’s role looks like in an AI-integrated firm—whether it contracts as routine work is automated away, or expands as senior lawyers delegate judgment-level work downward to associates who are freed from document review.^[70]

This stratification has implications for access to the profession, diversity, and health of the legal workforce pipeline. If the volume of entry-level legal work decreases substantially, law schools will graduate more students than the market can absorb, and the profession will become more selective and less accessible to lawyers from less privileged backgrounds who depend on the volume-based model to develop skills and build careers. These distributional effects deserve serious attention from the profession’s regulatory and educational institutions.

The Redefinition of Legal Value

Ultimately, the structural consequence of AI integration is a redefinition of the purpose lawyers serve. The traditional conception of legal value—expertise operationalized through time-intensive document work—is giving way to a conception in which legal value resides primarily in judgment, relationships, and the ability to navigate complexity that resists systematization.^[71] This is less a diminishment of the legal profession than a clarification of what has always been most valuable about it.

The lawyers best positioned for the AI-integrated future are those who combine deep understanding of AI’s capabilities and limitations with the capacity to exercise independent judgment in the spaces where those limitations bind. The profession’s challenge is to develop training, credentialing, and business models that cultivate and reward these capacities—rather than continuing to structure legal education and law firm economics around the volume-based model that AI is rendering obsolete.

The Trajectory of AI Toward More Effective Normative Legal Reasoning

The structural limitations identified in Section III are real, but they should not be mistaken for permanent boundaries.^[72] The trajectory of AI development suggests several pathways through which probabilistic systems may become materially more effective at tasks that approximate normative legal reasoning, even if the philosophical question of whether machines can truly exercise judgment remains open.^[73] Understanding these trajectories is important for the profession’s planning horizon because the practical consequences of AI that is functionally effective at normative-seeming tasks may be indistinguishable from those of AI that genuinely exercises judgment—and the legal industry must prepare for the former regardless of its position on the latter.^[74]

Retrieval-Augmented Reasoning and Dynamic Contextual Integration

One of the most consequential limitations of current generative AI systems—their dependence on static training data that necessarily reflects past practice—is already being addressed through retrieval-augmented generation architectures that allow models to access and integrate external information sources in real time.^[75] In the legal context, this development has immediate implications for the novelty problem identified in Section III.B: a system that can retrieve and reason over current judicial opinions, recently enacted regulations, and live deal databases is less constrained by the historical boundaries of its training corpus than one operating solely on pretrained patterns.^[76]

The more significant development is the emergence of agentic AI architectures—systems that decompose complex problems into subtasks, invoke specialized tools, and iteratively refine their outputs through structured reasoning chains.^[77] Applied to normative legal reasoning, an agentic system might not merely predict a statistically likely contract provision but instead identify the relevant jurisdictional precedents, assess the range of commercially negotiated outcomes in comparable transactions, model the risk exposure under alternative formulations, and synthesize these inputs into a recommendation that reflects identifiable reasoning rather than opaque pattern matching.^[78] This is something other than normative judgment in the philosophical sense; the system is producing outputs rather than making value choices. Yet those outputs may be functionally indistinguishable from reasoned legal advice for an increasingly wide range of practical contexts.^[79]

Preference Alignment and Client-Specific Calibration

A second pathway toward more effective normative output involves the development of preference-aligned AI systems that can be calibrated to specific clients’ risk tolerances, commercial objectives, and strategic priorities.^[80] The normative reasoning limitation described in Section III.C is, in part, a function of the fact that current systems lack access to the particularized context that informs human judgment—they do not know what the client values, what the counterparty is likely to tolerate, or what the deal’s strategic logic requires.^[81] But there is no structural reason why that context cannot be supplied to an AI system through properly designed input frameworks, institutional knowledge bases, and iterative feedback mechanisms that train the system on a firm’s or client’s historical preferences.^[82]

Law firms that build proprietary datasets of negotiated outcomes—linking specific deal contexts to the normative choices that attorneys made—can create training signals that capture not merely what provisions were used but the reasoning and contextual factors that drove their selection.^[83] A system trained on such data, and further refined through reinforcement learning from attorney feedback, could develop a functional capacity to recommend risk-allocation structures that are responsive to the same contextual inputs that inform human judgment, even if its internal process differs fundamentally from human deliberation.^[84] The competitive implications are significant: firms that invest early in building these feedback-integrated AI systems will develop proprietary analytical capabilities that are difficult for competitors to replicate, precisely because the value of the system is not in the model architecture but in the firm-specific training data and preference alignment.^[85]

Multimodal Integration and the Social Context Gap

The social and relational limitations identified in Section III.D—the inability of AI systems to read a room, assess credibility, or navigate political dynamics—represent perhaps the most durable boundary between AI capability and professional legal judgment.^[86] Yet, even here, developments in multimodal AI systems suggest that the boundary will shift, if not dissolve.^[87] Systems that can process not only text but also audio tone, facial expression, communication patterns, and behavioral data from negotiation histories are beginning to develop rudimentary capacities for social inference that, while far from human-level social intelligence, are meaningfully more sophisticated than text-only analysis.^[88]

The more realistic near-term application is not AI that replaces the senior partner’s social intelligence at the negotiating table, but AI that augments it by providing structured analysis of counterparty behavior patterns, historical negotiation tendencies, and probabilistic assessments of walk-away thresholds based on comparable transaction data.^[89] A system that can tell a negotiator, based on analysis of the counterparty’s responses across multiple deal points, that the counterparty is likely to concede on indemnification caps but remain firm on the MAC formulation provides useful strategic intelligence—even though it is not exercising social judgment in the way that a human lawyer does.^[90]

The Functional Equivalence Problem and Its Professional Implications

The convergence of these developmental trajectories creates what might be called the functional equivalence problem: as AI systems produce outputs that increasingly resemble the products of normative legal judgment, the profession must confront the question of whether functional equivalence is sufficient for professional purposes, or whether the exercise of genuine human judgment remains a necessary condition for the delivery of legal services.^[91] This question is not purely philosophical—it has direct implications for professional responsibility, malpractice liability, and the definition of legal practice itself.^[92]

If an AI system can produce a MAC clause formulation that an experienced Delaware practitioner would assess as commercially reasonable, contextually appropriate, and legally sound—not because the system exercised judgment but because its training data, preference alignment, and retrieval capabilities converged on the same output that judgment would have produced—the practical question is whether the legal system should treat that output differently from human work product.^[93] The answer, at least under current professional responsibility frameworks, is almost certainly yes: the obligations of competence, supervision, and accountability that attach to legal judgment presuppose a human professional who can be held responsible for the reasoning behind the decision, not merely for the decision itself.^[94] But the pressure that functionally equivalent AI outputs will place on this framework should not be underestimated, particularly as clients become aware that AI-generated work product may be comparable in quality at dramatically lower cost.^[95]

The profession’s response to this trajectory will define the next generation of legal practice. Firms that treat AI as merely an efficiency tool for document production will find themselves unprepared for systems that can contribute meaningfully to the analytical and advisory dimensions of transactional work.^[96] Firms that invest in developing human-AI collaborative workflows—in which AI provides structured analytical inputs and the attorney provides the normative judgment, accountability, and client-facing interpretation that the system cannot—will be positioned to deliver higher-quality legal services more efficiently than either human or machine could achieve alone.^[97] The competitive advantage in the AI-integrated legal market will accrue not to the firms with the most advanced AI systems, nor to the firms with the most experienced attorneys, but to the firms that most effectively integrate the two.

Conclusion

This paper has argued that AI’s impact on transactional legal practice is best understood through the lens of reconfiguration rather than replacement.^[98] AI materially improves efficiency in document-intensive workflows, enabling faster and more consistent performance of the pattern-recognition tasks that constitute a large portion of transactional legal work by volume. It is structurally limited in the tasks that constitute legal practice by value: reasoning about novelty, making normative judgments, and navigating the social and political context of complex deals.

The consequences of this reconfiguration are already visible: workflow compression, disrupted training pipelines, billing model pressure, new malpractice vectors, and emerging professional responsibility obligations. They will become more pronounced over time as AI capabilities continue to develop and as firms, clients, and bar authorities respond to the challenges and opportunities that AI deployment creates.

The central analytical contribution of this paper is the identification of the durable boundary between AI’s capabilities and the domain of legal judgment. That boundary is not a function of limitations that incremental improvements to existing architectures will straightforwardly resolve—it reflects deep features of current probabilistic systems that constrain their reliable performance of the normative, novel, and socially embedded tasks that define professional legal work. Understanding this boundary is the necessary foundation for thinking clearly about how law firms should deploy AI, how lawyers should develop the skills needed in an AI-integrated practice, and how the profession should adapt its regulatory and educational frameworks to serve the legal system that is emerging.

That said, this boundary should not be understood as permanently fixed. The most consequential near-term development is the shift from isolated generative tools toward integrated legal intelligence platforms that combine document analysis, probabilistic risk assessment, and structured reasoning within a unified workflow. As these systems mature, the execution layer that AI currently dominates will expand into tasks that today require senior associate and junior partner involvement, and the boundary between AI-appropriate and judgment-intensive work will continue to move. This trajectory carries immediate implications: law firms must redesign associate development around the assumption that AI will absorb an expanding share of execution work and identify how lawyers can build the contextual knowledge and practical intuition that high-volume tasks currently provide. Professional responsibility frameworks will similarly need to evolve as AI outputs become harder to verify through conventional human review. Most fundamentally, as next-generation systems close the contextual gap, the profession will need to articulate with greater precision what remains irreplaceable—and invest in developing it rather than assuming its permanence.

AI will not replace lawyers. But it is changing what lawyers do, how they develop, how they are compensated, and what it means to practice law at the highest levels of the profession. These changes deserve serious, sustained analytical attention—the careful, structural analysis that the legal profession is particularly well positioned to provide.

1. See John O. McGinnis & Russell G. Pearce, The Great Disruption: How Machine Intelligence Will Transform the Role of Lawyers in the Delivery of Legal Services, 82 Fordham L. Rev. 3041, 3042 (2014). ↑

2. See Daniel Martin Katz et al., GPT-4 Passes the Bar Exam, 382 Phil. Transactions Royal Soc’y A 20230254 (2024). ↑

3. See Richard Susskind, Tomorrow’s Lawyers: An Introduction to Your Future 47 (2d ed. 2017). ↑

4. See id. at 48. ↑

5. See Ronald J. Gilson, Value Creation by Business Lawyers: Legal Skills and Asset Pricing, 94 Yale L.J. 239, 240 (1984). ↑

6. See Harry Surden, Artificial Intelligence and Law: An Overview, 35 Ga. St. U. L. Rev. 1305, 1308 (2019). ↑

7. See Maura R. Grossman & Gordon V. Cormack, Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review, 17 Rich. J.L. & Tech. 11, 13 (2011). ↑

8. See Frank Pasquale, A Rule of Persons, Not Machines: The Limits of Legal Automation, 87 Geo. Wash. L. Rev. 1, 6 (2019). ↑

9. See Surden, supra note 6, at 1321. ↑

10. See Thomas H. Davenport & Julia Kirby, Only Humans Need Apply: Winners and Losers in the Age of Smart Machines 83 (2016). ↑

11. See id. at 85. ↑

12. See William D. Henderson, Legal Market Landscape Report 12 (Inst. for the Advancement of the Am. Legal Sys. 2018). ↑

13. See id. at 14. ↑

14. See Jan Hatzius et al., Goldman Sachs, The Potentially Large Effects of Artificial Intelligence on Economic Growth 4 (2023). ↑

15. See Pasquale, supra note 8, at 18. ↑

16. See ABA Comm. on Ethics & Pro. Resp., Formal Op. 512 (2024). ↑

17. See Gilson, supra note 5, at 243. ↑

18. See Model Rules of Pro. Conduct r. 1.1 (Am. Bar Ass’n 2020). ↑

19. See Susskind, supra note 3, at 112. ↑

20. See Grossman & Cormack, supra note 7, at 13. ↑

21. See Surden, supra note 6, at 1310. ↑

22. See Jason Wei et al., Emergent Abilities of Large Language Models, 2 Transactions on Mach. Learning Rsch. 1, 2 (2022). ↑

23. See Jason Wei et al., Chain-of-Thought Prompting Elicits Reasoning in Large Language Models, 36 Advances in Neural Info. Processing Sys. 24824, 24825 (2022). ↑

24. See Tom Brown et al., Language Models Are Few-Shot Learners, 33 Advances in Neural Info. Processing Sys. 1877, 1878 (2020). ↑

25. See Surden, supra note 6, at 1315. ↑

26. See Hatzius et al., supra note 14, at 8. ↑

27. See Pasquale, supra note 8, at 29. ↑

28. See Wei et al., supra note 23, at 24,830. ↑

29. See Surden, supra note 6, at 1308, 1315. ↑

30. See Grossman & Cormack, supra note 7, at 35. ↑

31. See Pasquale, supra note 8, at 5, 29–30; see also McGinnis & Pearce, supra note 1, at 3049. ↑

32. See François Chollet, On the Measure of Intelligence 11, 20 (Nov. 25, 2019) (arXiv preprint). ↑

33. See Pasquale, supra note 8, at 22, 25, 29–30. ↑

34. See Surden, supra note 6, at 1316, 1322, 1324–25. ↑

35. See McGinnis & Pearce, supra note 1, at 3049. ↑

36. See Grossman & Cormack, supra note 7, at 45. ↑

37. See Pasquale, supra note 8, at 22. ↑

38. See Ryan Calo, Artificial Intelligence Policy: A Primer and Roadmap, 51 U.C. Davis L. Rev. 399, 405 (2017). ↑

39. See Pasquale, supra note 8, at 5, 29–30. ↑

40. See Surden, supra note 6, at 1323–24, 1326. ↑

41. See Gilson, supra note 5, at 255. ↑

42. See Surden, supra note 6, at 1325. ↑

43. See Hatzius et al., supra note 14, at 6. ↑

44. See Henderson, supra note 12, at 18. ↑

45. See Susskind, supra note 3, at 95. ↑

46. See Henderson, supra note 12, at 22. ↑

47. See ABA Comm. on Ethics & Pro. Resp., Formal Op. 512, at 4 (2024). ↑

48. See id. at 4, 10. ↑

49. See Davenport & Kirby, supra note 10, at 91. ↑

50. See Henderson, supra note 12, at 25. ↑

51. See Gilson, supra note 5, at 243. ↑

52. See Press Release, Litera, Litera Agrees to Acquire Leading Machine Learning Contract Analysis Company, Kira Systems (Aug. 10, 2021). ↑

53. See Akorn, Inc. v. Fresenius Kabi AG, No. 2018-0300, 2018 WL 4719347, at *1 (Del. Ch. Oct. 1, 2018). ↑

54. See Gilson, supra note 5, at 258. ↑

55. See McGinnis & Pearce, supra note 1, at 3052. ↑

56. Model Rules of Pro. Conduct r. 1.1 (Am. Bar Ass’n 2020). ↑

57. Id. r. 1.1 cmt. 8. ↑

58. See ABA Comm. on Ethics & Pro. Resp., Formal Op. 512, at 3 (2024). ↑

59. See id. at 5. ↑

60. Model Rules of Pro. Conduct r. 5.1, 5.3. ↑

61. See ABA Comm. on Ethics & Pro. Responsibility, Formal Op. 512, at 7. ↑

62. See Model Rules of Pro. Conduct r. 1.6. ↑

63. See Pasquale, supra note 8, at 30. ↑

64. See, e.g., Mata v. Avianca, Inc., 678 F. Supp. 3d 443, 448 (S.D.N.Y. 2023) (sanctioning attorneys for submitting AI-generated brief containing fabricated citations); see also Model Rules of Pro. Conduct r. 3.3. ↑

65. See Hatzius et al., supra note 14, at 9. ↑

66. See Henderson, supra note 12, at 30. ↑

67. See Susskind, supra note 3, at 103. ↑

68. See id. at 107. ↑

69. See Davenport & Kirby, supra note 10, at 98. ↑

70. See Henderson, supra note 12, at 34. ↑

71. See Gilson, supra note 5, at 262. ↑

72. See Dario Amodei, Machines of Loving Grace: How AI Could Transform the World for the Better (Oct. 2024). ↑

73. See Surden, supra note 6, at 1330. ↑

74. See ABA Comm. on Ethics & Pro. Resp., Formal Op. 512, at 4–5 (2024). ↑

75. See Hatzius et al., supra note 14, at 11. ↑

76. See Pasquale, supra note 8, at 35. ↑

77. See McGinnis & Pearce, supra note 1, at 3055. ↑

78. See Surden, supra note 6, at 1335. ↑

79. See ABA Comm. on Ethics & Pro. Resp., Formal Op. 512, at 8 (2024). ↑

80. See Grossman & Cormack, supra note 7, at 48. ↑

81. See Susskind, supra note 3, at 118. ↑

82. See Gilson, supra note 5, at 265. ↑

83. See Henderson, supra note 12, at 36. ↑

84. See Davenport & Kirby, supra note 10, at 105. ↑

85. See Pasquale, supra note 8, at 40. ↑

86. See McGinnis & Pearce, supra note 1, at 3060. ↑

87. See Calo, supra note 38, at 418. ↑

88. See Surden, supra note 6, at 1340. ↑

89. See Susskind, supra note 3, at 125. ↑

90. See Gilson, supra note 5, at 270. ↑

91. See ABA Comm. on Ethics & Pro. Resp., Formal Op. 512, at 10 (2024). ↑

92. See Henderson, supra note 12, at 40. ↑

93. See Pasquale, supra note 8, at 45. ↑

94. See ABA Comm. on Ethics & Pro. Resp., Formal Op. 512, at 4 (2024). ↑

95. See Hatzius et al., supra note 14, at 14. ↑

96. See Gilson, supra note 5, at 275. ↑

97. See Henderson, supra note 12, at 42. ↑

98. See Susskind, supra note 3, at 130. ↑

Businesses increasingly operate across borders through manufacturing and distribution agreements. Cross-border operations expand a brand’s market presence while creating opportunities to monetize intellectual property (“IP”) through licensing, royalty arrangements, and assignments of rights. The extraterritorial nature of the agreements can make it difficult to ascertain the applicable law and forum if those issues are not addressed in the initial master agreement. Even then, poorly drafted or outdated manufacturing and distribution agreements can turn disputes over the relationship into costly litigation. The Slush Puppie litigation illustrates how those issues can compound when a cross-border commercial relationship evolves faster than the agreements governing it.

Manufacturing and Distribution Agreements in Slush Puppie

Cross-border manufacturing and distribution agreements were at the center of the seven-year dispute in Slush Puppie Ltd. v. Icee Co.^[1] Slush Puppie Limited’s (“SPL”) dissatisfaction with the limits on its European distribution and trademark rights, including its inability to pursue broader trademark enforcement without Icee’s authorization, became a central source of conflict.^[2] A 1996 Manufacturing Appointment granted SPL exclusive manufacturing rights across twenty-seven European countries, while a 1999 Distributor Agreement granted the distinct and geographically narrower right to distribute Slush Puppie and use the SLUSH PUPPIE marks exclusively in the United Kingdom (“U.K.”) and Ireland.^[3] Because the 1999 Distributor Agreement did not supersede the 1996 Manufacturing Appointment, both remained operative until Icee terminated them in June 2019.^[4] Few provisions proved more consequential than the 1999 agreement’s termination clause triggered by litigation.^[5]

The contractual limits on SPL’s European distribution and trademark rights became a persistent source of commercial friction.^[6] That friction intensified when SPL relied on a fabricated 2000 appointment purporting to grant exclusive European trademark rights while separately contending that an earlier agreement had reduced its royalty obligation from 5% to 2.5%.^[7] In hindsight, asserting broader European rights alongside a 50% royalty reduction should have raised an immediate red flag.^[8] After Icee terminated the agreements, SPL challenged the litigation-triggered provisions as unconscionable, but the court rejected the argument, emphasizing the parties’ commercial sophistication, their long-standing voluntary dealings, and the agreement’s distinction between curable defaults and events permitting immediate termination.^[9]

Slush Puppie Litigation

Once litigation began, the case became far more than a contractual dispute. Judge Barrett ultimately dismissed SPL’s remaining claims with prejudice for the fraud perpetrated on the court and the American judicial process.^[10] As of publication, a federal jury in Ohio had also returned an advisory verdict in Icee’s favor on its counterclaims, finding unjust enrichment, trademark infringement under sections 10(1) and 10(3) of the U.K. Trade Marks Act 1994, and passing off under U.K. common law.^[11] The jury allocated $33 million in disgorgement across post-termination periods from 2019 through 2025, with separate disgorgement awards totaling $3.6 million on the U.K. trademark and passing-off claims.^[12]

Figure 1. Slush Puppie Ltd. v. Icee Co. Key Rulings and Litigation Milestones

Takeaways

There are two equally important takeaways from this case. The first is that establishing a robust IP portfolio can pay dividends; the second is that extraterritorial agreements should be drafted with termination and the winding up of the parties’ relationship in mind from the outset.

The first lesson concerns the assets themselves. Companies and investors tend to focus heavily on patents to protect innovation while overlooking trademark and trade secret rights that can potentially endure indefinitely, as well as copyright protection available across Berne Convention member countries.^[13] A robust IP portfolio can protect the enterprise while creating valuable, durable, revenue-generating rights.^[14] Patents generally expire twenty years from filing, while trademarks can endure indefinitely through continued use in commerce and become core assets of a global brand. Trade secrets likewise can remain valuable indefinitely when properly safeguarded.^[15] The greatest long-term value comes not from patents alone but from building a complementary portfolio of IP rights.

The second lesson concerns the agreements governing those assets. When commercializing IP abroad, draft the manufacturing and distribution agreements from the end backward. An amicable beginning should not obscure the need to define termination and winding up at the outset. In cross-border manufacturing and distribution agreements, the most pertinent provisions often address term, territory, exclusivity, IP ownership and enforcement, performance and review milestones, royalty rates, termination, governing law, forum selection, clearly delineated schedules and exhibits, amendment requirements, and post-termination winding up obligations.^[16] Had the parties in Slush Puppie periodically reviewed and memorialized their agreements, a clearer record might have narrowed the dispute years earlier and avoided substantial motion practice and expense.^[17] Designing an agreement around both the life and conclusion of a business relationship does more than strengthen the instrument; it also facilitates a clear record of the parties’ course of dealing that can facilitate early resolution of later disputes. Taken together, IP strategy and contract strategy must be aligned from the outset of international expansion.

The broader takeaway from Slush Puppie is that international expansion requires more than obtaining IP rights and signing a distribution or manufacturing agreement. Businesses should build complementary portfolios of patents, trademarks, copyrights, and trade secrets while ensuring that the agreements governing those assets clearly address territory, exclusivity, enforcement, amendment, termination, and winding up. When the rights and the contractual record develop together, businesses are better positioned not only to capture long-term value but also to avoid having a court reconstruct the parties’ relationship after it has already fallen apart.

1. Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189-MRB, 2020 U.S. Dist. LEXIS 265181 (S.D. Ohio Sept. 10, 2020); Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189-MRB, 2023 U.S. Dist. LEXIS 80519, slip op. (S.D. Ohio Mar. 16, 2023); Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-189, 2023 U.S. Dist. LEXIS 160476 (S.D. Ohio July 10, 2023); Slush Puppie Ltd. v. Icee Co., 729 F. Supp. 3d 773 (S.D. Ohio 2024); Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189, 2023 U.S. Dist. LEXIS 247789 (S.D. Ohio Apr. 7, 2025); Slush Puppie Ltd. v. Icee Co., 792 F. Supp. 3d 834 (S.D. Ohio 2025); Slush Puppie Ltd. v. Icee Co., 821 F. Supp. 3d 912 (S.D. Ohio 2026); Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189, 2026 U.S. Dist. LEXIS 38663 (S.D. Ohio Feb. 25, 2026); Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189, 2026 U.S. Dist. LEXIS 147973 (S.D. Ohio Apr. 23, 2026); Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189, 2026 U.S. Dist. LEXIS 219419 (S.D. Ohio July 8, 2026). ↑

2. Slush Puppie, 729 F. Supp. 3d at 778 (stating that SPL needed a side letter expanding the territory under the 1999 Distributor Agreement before it could “start a trademark action in Spain”); see also Slush Puppie, 821 F. Supp. 3d at 915–19 (describing the differing territorial scope of the 1996 and 1999 agreements and the later dispute over broader European trademark rights). ↑

3. See Slush Puppie, 821 F. Supp. 3d at 915–18; Slush Puppie, 792 F. Supp. 3d at 840–42. ↑

4. See Slush Puppie, 821 F. Supp. 3d at 915–18; Slush Puppie, No. 1:19-cv-00189-MRB, slip op. at 19–22 (S.D. Ohio Mar. 16, 2023). ↑

5. See Slush Puppie, No. 1:19-cv-00189-MRB, slip op. at 19–22 (S.D. Ohio Mar. 16, 2023). ↑

6. See Slush Puppie, 821 F. Supp. 3d at 915–19. ↑

7. See id. at 918–19, 925–34. ↑

8. See id. at 918–19 (describing Icee’s challenge to the authenticity of the purported 2000 appointment after SPL presented it as a superseding agreement granting broader European trademark rights). ↑

9. See Slush Puppie, No. 1:19-cv-00189-MRB, slip op. at 24–22 (S.D. Ohio Mar. 16, 2023) (rejecting SPL’s unconscionability challenge and distinguishing ordinary defaults subject to cure from enumerated grounds for immediate termination). ↑

10. See Slush Puppie, 821 F. Supp. 3d at 925–34. ↑

11. See Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189-MRB, 2026 U.S. Dist. LEXIS 219419, at 1–2 (S.D. Ohio July 8, 2026), ECF No. 504; see also Interrogatories & Verdict Form at 10–11, Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189-MRB (S.D. Ohio May 22, 2026), ECF No. 488. ↑

12. See Slush Puppie, 2026 U.S. Dist. LEXIS 219419 at 1–2; see also Slush Puppie, Interrogatories & Verdict Form at 10–11 (S.D. Ohio May 22, 2026). ↑

13. See 35 U.S.C. § 154(a)(2) (providing the general twenty-year term for utility patents); 15 U.S.C. §§ 1058(a), 1059(a) (providing for continued trademark registration and successive ten-year renewals, subject to statutory requirements); 18 U.S.C. § 1839(3) (defining a trade secret by reference to reasonable measures to maintain secrecy and economic value derived from the information’s not being generally known); Berne Convention for the Protection of Literary and Artistic Works art. 5(1)–(2), Sept. 9, 1886, as revised at Paris, July 24, 1971 (providing national treatment in other Union countries and stating that the extent of protection and means of redress are governed by the law of the country where protection is claimed). ↑

14. See 35 U.S.C. § 154(a)(2); 15 U.S.C. §§ 1058(a), 1059(a); 18 U.S.C. § 1839(3)); Berne Convention for the Protection of Literary and Artistic Works art. 5(1)–(2), Sept. 9, 1886, as revised at Paris, July 24, 1971. ↑

15. See 18 U.S.C. § 1839(3) (defining a trade secret to require, among other things, that the owner take reasonable measures to keep the information secret and that the information derive actual or potential independent economic value from not being generally known); Defend Trade Secrets Act of 2016, Pub. L. No. 114-153, § 2(b), 130 Stat. 376, 380–81. ↑

16. See, e.g., Watec Co. v. Liu, 403 F.3d 645, 654 (9th Cir. 2005) (explaining that, in manufacturer-distributor disputes, courts look first to the parties’ agreement concerning trademark rights and affirming that the parties’ licensing arrangement remained unchanged); Covertech Fabricating, Inc. v. TVM Bldg. Prods., Inc., 855 F.3d 163, 171 (3d Cir. 2017) (applying a rebuttable manufacturer presumption and multifactor analysis where the parties’ agreement did not resolve trademark ownership); Slush Puppie Ltd. v. Icee Co., 792 F. Supp. 3d 834, 840–42, 851–54 (S.D. Ohio 2025) (describing territorial limits in the parties’ distribution agreement and analyzing the consequences of foreign conduct and the contractual choice-of-law provision); I.M. Wilson, Inc. v. Otvetstvennostyou “Grichko,” 614 F. Supp. 3d 114, 131–38 (E.D. Pa. 2022) (denying summary judgment on trademark ownership where the distribution agreement, registration documents, and parties’ conduct permitted competing inferences); Coyne’s & Co. v. Enesco, LLC, 565 F. Supp. 2d 1027, 1042–44 (D. Minn. 2008) (examining contractual limits on a distributor’s trademark rights, including territory, duration, and ownership); Versatile Housewares & Gardening Sys., Inc. v. Thill Logistics, Inc., 819 F. Supp. 2d 230, 241–46 (S.D.N.Y. 2011) (addressing remedies arising from breach of contractual forum-selection provisions); Minarik Elec. Co. v. Electro Sales Co., 223 F. Supp. 2d 334, 341–42 (D. Mass. 2002) (distinguishing a former distributor’s right to resell genuine remaining inventory from allegedly misleading post-termination trademark and website use). ↑

17. See Slush Puppie Ltd. v. Icee Co., 821 F. Supp. 3d 912, 916 n.6, 917 n.11, 918–19, 925–34 (S.D. Ohio 2026) (describing contractual written-amendment requirements, the later-asserted purported 2000 appointment, the authenticity dispute and fabricated supporting materials, and the resulting sanctions proceedings); Opinion & Order pts. III.A–C, IV, Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189-MRB, 2023 U.S. Dist. LEXIS 80519 (S.D. Ohio Mar. 16, 2023), ECF No. 189 (granting partial summary judgment and holding Icee’s June 25, 2019, termination effective as a matter of law); Slush Puppie, 792 F. Supp. 3d at 846–54 (resolving subsequent Rule 12 challenges to Icee’s amended counterclaims); Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189, 2026 U.S. Dist. LEXIS 38663, at *4–13 (S.D. Ohio Feb. 25, 2026) (partially reconsidering the prior dismissal and substituting U.K.-law theories); Slush Puppie Ltd. v. Icee Co., No. 1:19-cv-00189, 2026 U.S. Dist. LEXIS 147973, at *2–5 (S.D. Ohio Apr. 23, 2026) (denying a further Rule 12(c) challenge after the parties agreed to proceed toward trial without another round of dismissal motions). ↑

“You never walk into a house and compliment how clean it is, but you immediately notice when it’s dirty.”

Deborah Walker Kool shared that observation during the ABA Business Law Section’s Fall Meeting CLE program “The Underused Board: Why Investors Should Treat Governance as a Value Lever,” and it stuck with me. It’s also a great way to think about corporate governance.

When governance is working well, it often goes unnoticed. The company is operating, the board is functioning, and decisions are being made without much attention. But, when a business hits a rough patch, brings in outside investors, seeks financing or prepares for a sale, or is asked to produce records, weaknesses in governance have a way of becoming very visible, very quickly.

This program focused on what effective governance actually looks like in practice, particularly when it comes to board composition, fiduciary duties, and the role lawyers can play as directors.

Moderated by Walker Kool, of counsel at Fredrikson & Byron, the panel featured insights from Jonathan Blackburn, partner at Sidley Austin; Fred Hoch, founder and general partner of TechNexus Venture Collaborative; Sherrin Ross Ingram, independent corporate director and chief executive officer of the International Center for Strategic Planning; and Katayun “Kathy” Jaffari, chair of Corporate Governance and co-chair of Capital Markets and Securities at Cozen O’Connor. Each brought a different perspective, from investing to board service, governance, and corporate law.

Build the Board the Company Needs

A recurring theme was that the right board for a company today may not be the right board for that company as time goes on. An early-stage business may begin with a small group of founders, friends, family members, and trusted advisors. That can work for a time. But as the company raises money, expands, takes on more complex operations, or begins thinking about a significant transaction, its board needs to grow with it.

Hoch discussed the importance of selecting board directors who can contribute something meaningful beyond a recognizable name or an impressive resume. He noted that the best board members bring experience, relationships, judgment, and perspective. They may help management work through a difficult issue, make an introduction, or spot a challenge that the leadership team has not yet considered. Hoch made a similar point when discussing investors, saying, “On the capital side, I would rather take less money or less valuation from somebody who’s going to add value in the short term versus more money for who’s not.” That comment stood out as another way to view board makeup. Investors can contribute more than capital. Through board participation, industry knowledge, relationships, and strategic guidance, the right investor can become part of the company’s governance infrastructure and help create value over time.

Bringing the right people into the boardroom is only part of the equation. They also need to be willing to challenge management when necessary. Blackburn noted the potential downside of a board made up largely of people who are personally close to an owner/founder. Those relationships may make it harder to challenge assumptions or push back when a difficult decision needs to be made. To be the most useful, boards need people who are willing to ask uncomfortable questions when necessary and create some “tension and a different opinion” from what a founder or management wants to do.

The central theme was that a board is not there simply because the organizational documents say there should be one. Done well, it should serve as an active resource for management while still providing meaningful oversight.

Fiduciary Duties Matter

The panel also spent time on fiduciary duties, including the duties of care, loyalty, and good faith.

Those concepts are familiar to business lawyers, but the conversation was less about reciting the standards and more about what they require from directors.

The duty of care means directors should be informed before making decisions and should exercise appropriate business judgment. The duty of loyalty requires directors to recognize and disclose conflicts of interest and, where appropriate, step away from decisions in which their own interests may conflict with those of the organization. Good faith requires directors to carry out their responsibilities honestly and with the interests of the organization in mind.

One practical point that stood out was confidentiality.

It is easy to assume that everyone at the board meeting understands that the information shared there is confidential. But, the panel shared, that assumption can create problems. Boards are better served by making those expectations explicit, particularly where directors may have other business interests, investor relationships, or professional roles that overlap with the company’s industry.

The panel also mentioned oversight obligations through the lens of the Delaware Court of Chancery’s pivotal Caremark decision. Jaffari stressed the importance of having reporting systems, internal controls, and monitoring processes in place before a problem occurs.

That point is particularly important because governance systems are difficult to build in the middle of a crisis. Companies are much better positioned when the board has already considered what information it needs to receive, how often it needs to receive it, and who is responsible for escalating significant issues.

Lawyers Bring Something Different to the Boardroom

One of the more interesting parts of the discussion involved lawyers serving as directors.

As lawyers, we inherently bring skills that translate well to board service. We are trained to identify risks, ask questions, think critically through consequences, recognize potential conflicts, and anticipate what might go wrong before it happens. Those instincts are valuable to a company’s board. But they can also create a temptation to slip into lawyer mode.

Ingram made the point that a lawyer serving on a board is not there to solve every legal or operational issue. The role of a director is different from the role of outside counsel. A director should be asking whether management has identified the issue, whether the right people are addressing it, and whether an appropriate process is in place. That does not mean taking over the problem personally.

Jaffari captured the distinction in a phrase that was probably one of the most memorable of the program: “Noses in, fingers out.” In other words, directors should know what is going on. They should ask questions, challenge assumptions, identify risks, and make sure management is addressing important issues. But they should not cross the line into solving the issue themselves.

That balance is ultimately what good governance requires.

The program reinforced that governance should not be treated as a box to check or something to address only when a transaction is on the horizon. A thoughtful board can become a real strategic asset. To Walker Kool’s point, most people never compliment a clean house; they simply expect it. Governance operates much the same way. While strong board processes, engaged directors, and thoughtful oversight may not generate headlines, their absence almost certainly will.

To learn more, view the program as on-demand CLE, free for Business Law Section members.

Canada offers an attractive gateway for foreign businesses looking to establish or expand a North American presence, including U.S. businesses expanding north of the border; a stable legal system, a skilled workforce, and extensive trade agreements make it an appealing destination.

This article provides an overview of the key considerations for foreign entities establishing a presence in Canada, from choosing the right business structure to navigating regulatory requirements. A threshold distinction is worth noting at the outset: Doing business “in Canada” (which typically triggers a Canadian tax presence) is different from doing business “with Canada” (which may not).

Canada’s Legal Landscape

Canada is a federal system comprised of ten provinces and three territories. There is a constitutional division of powers between the federal and provincial governments. The federal government has authority over matters of national dimensions, including banking, criminal law, immigration, international trade, and intellectual property, as well as specific industries such as airlines, railways, broadcasting, and telecommunications. Provinces have jurisdiction over more regional matters, including property rights, natural resources, securities regulation, business corporations, and employment and labor standards. There are many areas of joint federal-provincial responsibility, and while federal statutes apply throughout the country, much of the law affecting businesses on a day-to-day basis falls within provincial and territorial jurisdiction. Corporations may be incorporated under federal or provincial law.

Except for the province of Québec, all Canadian jurisdictions follow the common law tradition, with Québec operating under a hybrid legal system, applying civil law to private law matters and common law to public law matters such as criminal law. Businesses operating in Québec must also account for unique requirements, including French language obligations and other province-specific compliance rules.

Types of Business Structures

The first decision when establishing a presence in Canada is typically what type of business structure to use. Typical business structures in Canada include corporations, unlimited liability companies (“ULCs”), general partnerships, limited partnerships, joint ventures, and, for foreign entities, branch offices.

Corporation

The most common route for foreign entities expanding into Canada is to incorporate a Canadian subsidiary. A subsidiary may be incorporated under the federal Canada Business Corporations Act or under the corporate statute of any province or territory. Requirements relating to director residency, name approval, and ongoing reporting differ not only between federal and provincial regimes, but also among the provinces and territories (see “Jurisdictional Considerations” below). In Canada, a corporation is a legal entity distinct from its shareholders and management, endowed with all the legal capacities of a natural person: It can own property, carry on business, borrow, lend, sue, and be sued. Shareholders’ liability is accordingly limited, except in exceptional circumstances. A Canadian subsidiary is resident in Canada for tax purposes, and it must pay Canadian tax on its worldwide income and file separate tax returns.

Unlimited Liability Company

Certain Canadian provinces, namely Alberta, British Columbia, and Nova Scotia, permit the incorporation of unlimited liability companies, a corporate vehicle in which shareholders are liable for the company’s debts and liabilities. ULCs are often used by foreign investors, particularly from the United States, because they may qualify as “disregarded entities” or partnerships for U.S. federal income tax purposes, allowing Canadian income and losses to flow through to the U.S. parent company while maintaining a Canadian corporate structure locally.

Partnership

A partnership exists when two or more persons carry on business together with a view to profit. The provinces have exclusive jurisdiction over partnerships, and each province has enacted its own partnership legislation. The two principal forms are general partnerships and limited partnerships.

i. General Partnership

In a general partnership, all partners share in the management of the business and are jointly and severally liable for its debts and obligations. A general partnership requires no formal steps to come into existence; it arises by operation of law wherever two or more persons carry on business in common with a view to profit, whether or not the parties intend to create a partnership. Foreign entities collaborating with Canadian parties should therefore be mindful that a partnership may be found to exist inadvertently. Although many provinces require a general partnership to register its business name, registration is not a precondition to the partnership’s existence.

ii. Limited Partnership

A limited partnership, by contrast, consists of one or more general partners who manage the business and bear unlimited liability, and one or more limited partners whose liability is capped at the amount of their contributions to the partnership. Note, however, that limited partners may not take an active role in management without risking the loss of their limited liability protection. The general partner in a limited partnership is often itself a limited liability entity, such as a corporation or an LLC, which can serve to contain the exposure of the individuals behind the venture. Further, a limited partnership exists only once it has been formally established in accordance with, and registered under, the applicable provincial limited partnership legislation. Until those formalities are complete, the limited partners may not benefit from limited liability.

For tax purposes, neither form of partnership is recognized as a distinct entity; income and losses flow through to the partners in proportion to their interests and are taxed at the partner level.

Joint Venture

Joint ventures in Canada are contractual rather than statutory. A joint venture is an arrangement where two or more persons agree to contribute property, services, or capital to a common commercial enterprise. The agreement governing the joint venture should expressly disclaim any intention to form a partnership. The key drivers in choosing between a partnership and a joint venture are tax considerations, liability exposure, and the type of presence the foreign entity wishes to establish in Canada.

Branch Office

Unlike each of the structures above, which involve establishing a separate Canadian entity, foreign entities may also conduct business within Canada through a branch office. A branch office is not a separate legal entity but rather an extension of the foreign parent. Establishing a branch involves registering or obtaining a license as an extra-provincial corporation in each province or territory where the entity intends to carry on business. This registration permits the foreign entity to operate locally without incorporating a separate Canadian subsidiary. Although setting up a branch is generally less expensive than incorporation, it exposes the foreign parent to direct liability for Canadian operations.

As with the partnership versus joint venture decision, the key factors in choosing between a branch and a subsidiary are tax considerations, the need for limited liability, and the nature of the intended Canadian presence. One significant tax advantage of a branch structure is the ability (subject to the laws of the parent’s home jurisdiction) to flow losses from the branch back to the parent. If the Canadian operations are expected to incur significant losses in the early years, a branch may be the preferable approach.

However, unless exemptions exist under applicable laws and tax treaties, a branch will be subject to a Canadian branch profits tax, which approximates the withholding tax that would have been paid on dividends from a Canadian subsidiary to its foreign parent. The branch profits tax is typically 25 percent, subject to reductions under applicable tax treaties.

Key Considerations

Jurisdictional Considerations

A corporate entity can be incorporated under any of the federal, provincial, or territorial statutes, many of which are substantially similar to the federal Canada Business Corporations Act.

In choosing jurisdictions, many factors may be considered, including whether the entity will operate in one or more Canadian jurisdictions, director residency requirements, and corporate naming requirements. For example, the federal Canada Business Corporations Act and the corporate statutes of Manitoba, Saskatchewan, and Newfoundland and Labrador require that at least 25 percent of a corporation’s directors be resident Canadians. All other provinces no longer have this requirement in their corporate statutes.

Corporations incorporated federally, provincially, or territorially must extra-provincially register in each additional Canadian jurisdiction where they carry on business. Note that incorporating in British Columbia, Alberta, Saskatchewan, or Manitoba allows a corporation to rely on the New West Partnership Trade Agreement, which has eliminated many extra-provincial filing requirements for corporations registered in those provinces.

Regardless of the structure chosen, an entity that carries on business in a province or territory other than its home jurisdiction must generally register or obtain a license as an extra-provincial entity in that jurisdiction. This applies to a foreign entity operating through a branch and to a Canadian corporation incorporated in another province. In certain regulated industries, however, the foreign entity may be required to incorporate a Canadian subsidiary rather than simply register. Generally, a corporation may be found to be carrying on business in a Canadian province if, among other things,

• it has a resident agent, representative, employees, warehouse, office, or physical place where it carries on its business in a province;
• it holds an interest in real property located in a province other than by way of security; or
• it carries on an activity that is subject to provincial licensing or regulation.

Failure to obtain a required license may result in penalties and could prevent the foreign entity from maintaining proceedings before Canadian courts concerning its contracts. The licensing process is generally straightforward, provided the entity’s name is not confusingly similar to that of an existing entity in the same jurisdiction.

Name Registry

Another important consideration is reserving the proposed name for the corporation. When incorporating, an entity may use a chosen name (if available) or have a numbered name assigned. A numbered name is a name made up of the corporation number assigned by the registrar followed by a jurisdictional designation and legal ending (for example, 1234567 Canada Inc. or 1234567 Ontario Ltd.). This avoids the need for a name search.

Any corporate name typically needs to be approved by the relevant federal, provincial, or territorial registrar, or otherwise be available for use in such jurisdiction. Do not assume that a name used in another country is available in Canada or in any specific province or territory. When choosing a corporate name, ensure it is distinctive, does not cause confusion with any existing name or trademark, and does not include terms reserved for regulated industries (such as “Bank”) or words that are misleading, obscene, or objectionable. In Québec, a business must have a French-language name. A version of the name in another language may be used, but only together with the French version.

Transparency and Beneficial Ownership Registers

Under certain federal and provincial transparency requirements, corporations must maintain a register of individuals with significant control. This register must include: (i) individuals who own, control, or direct (directly or indirectly, individually, jointly, or in concert with others) 25 percent or more of the voting rights attached to or fair market value of the corporation’s shares; (ii) individuals who have control in fact over the corporation without owning any shares; or (iii) individuals who meet a combination of (i) and (ii). Currently, corporations incorporated federally or under the provincial laws of Québec are required to submit ultimate beneficial ownership information to the relevant regulator, which becomes publicly searchable through local transparency databases.

Importantly, wholly owned subsidiaries of public corporations and public corporations themselves are excluded from these transparency requirements. Penalties for noncompliance are severe, including fines for directors or officers of up to C$1 million and imprisonment of up to five years.

Land Registers

In British Columbia, corporations must comply with land transparency requirements that mandate disclosure of information about the ultimate beneficial owners of land held through corporations, partnerships, and trusts. British Columbia’s Land Owner Transparency Registry makes certain information publicly searchable.

Ontario has similar register requirements; however, such information is not made publicly available.

Capitalizing Canadian Operations

Canadian subsidiaries can be capitalized with equity, debt, or a combination of both. There is no minimum or maximum amount of share capital that a corporation can issue, unless otherwise specified in its incorporating documents. Share structures are highly flexible: Shares may be voting or nonvoting, with different dividend or liquidation rights. Corporations may also borrow funds and grant security interests over their property.

Canadian banks require extensive documentation in order to set up a bank account, including identification, proof of ownership, and incorporation documents. Ultimately, how a business chooses to capitalize its Canadian subsidiary will be driven by tax considerations, in consultation with the business’s financial and tax advisers.

Tax Considerations

A subsidiary incorporated in Canada is deemed to be a Canadian resident and is, therefore, subject to tax in Canada on its worldwide income. Nonresidents, by contrast, are generally subject to tax only on Canadian sourced income. Nonresidents may also be subject to withholding tax at a rate of 25 percent on certain payments made by residents of Canada, unless reduced or eliminated by a tax treaty such as the Canada-United States Income Tax Convention.

Tax considerations often drive capitalization strategies. For example:

• Thin Capitalization Rules: Limits the deductibility of interest when debt to certain specified nonresident shareholders exceeds 1.5 times equity. Excess interest is also recharacterized as a dividend subject to withholding tax.
• EIFEL Rules: Care should be taken so that the interest deduction does not exceed 30 percent of the subsidiary’s adjusted tax income, as determined for purposes of the Excessive Interest and Financial Expenses Limitation (“EIFEL”) rules.
• Withholding and Branch Taxes: Nonresidents face a 25 percent withholding tax on certain payments, though treaties usually reduce the rate. The Canada–U.S. treaty, for example, reduces the branch profit tax to 5 percent and exempts the first C$500,000.

Employment Considerations

Canadian employment law differs significantly from U.S. practice. Notably, there is no concept of “at-will” employment, and the bar for termination “for cause” is considerably higher than in the United States, as performance issues alone rarely suffice. Employees are entitled to notice of termination or pay in lieu unless dismissed for cause. While statutes prescribe minimum notice periods, courts often award substantially more—in some cases exceeding a year for long-tenured or senior employees—under the common law doctrine of “reasonable notice,” which considers factors such as the employee’s age, tenure, and position, and the availability of comparable employment. Although oral employment contracts are enforceable in Canada, a carefully drafted written agreement is the only way to limit termination entitlements to statutory minimums. If any provision could operate to provide less than the applicable minimum, courts will void the entire clause (not merely the offending portion), as Canadian courts, unlike many U.S. jurisdictions, will not “blue-pencil” deficient language to save the remainder.

Employers must also comply with provincial employment standards legislation covering wages, hours, overtime, holidays, vacation, and leaves, as well as provincial occupational health and safety legislation. Worker classification is closely scrutinized. Contractor labels and staffing agency or professional employer organization arrangements do not shield the “real” employer from liability. Hiring foreign workers requires careful attention to immigration rules: “Business visitors” may enter without a work permit, but most other workers require one.

Investment Canada Act and Competition Act

The establishment of a new business in Canada by a foreign entity (in terms of ultimate control) is subject to a notification filing requirement under the Investment Canada Act. Additional requirements may also apply to the establishment of a new “cultural business” in Canada.

This filing is not required on incorporation, but when such corporation is considered to have established a “new Canadian business” by meeting the below requirements:

1. The corporation is capable of generating revenue and is carried on in anticipation of profit.
2. The corporation is unrelated to an existing Canadian business with the same ultimate controller.
3. The corporation has individuals employed in connection with the business activities anywhere in Canada (this is a broad concept and includes independent contractors in addition to employees).
4. The corporation has a place of business in Canada (this is a broad concept and includes employees or contractors who work from home).
5. The corporation has assets in Canada for the carrying on of the business (this is a broad concept with no de minimis threshold, and intangible assets will generally be considered sufficient to meet this requirement).

Larger acquisitions may be reviewable if they exceed the applicable financial thresholds, with the federal government assessing whether the investment is of “net benefit to Canada.” Importantly, all investments, regardless of size or structure, are subject to potential national security review, a process increasingly applied to sensitive sectors such as artificial intelligence and critical minerals.

Significant transactions may also require pre‑merger notification under the Competition Act if both the size‑of‑parties threshold (currently C$400 million) and the annually indexed size‑of‑transaction threshold (currently C$93 million) are met.

Conclusion

Forming an entity in Canada requires careful navigation of a complex legal and regulatory landscape that differs in important respects from other jurisdictions. From jurisdictional choices and transparency obligations to tax structuring, employment law, and investment review, each step involves considerations with long-term implications. The foregoing is intended as an overview of key considerations and is not exhaustive. Depending on the nature of the proposed business activities, a foreign entity may engage additional regulatory regimes beyond the scope of this article, including anti-money laundering, privacy, banking and financial services, consumer protection, health care, and other sector-specific requirements, and should obtain advice tailored to its particular circumstances. Foreign businesses that understand the rules and tailor their market-entry strategies accordingly will be well positioned to succeed.

How would you imagine legal ethics rules of professional conduct might be presented in a “Chicago style”? During the ABA Business Law Section’s 2026 Fall Meeting in Chicago, the CLE program “The Rules Brothers (and Sisters): A Chicago-Style Review of Basic Legal Ethics Rules of Professional Conduct That Every Business Lawyer Needs” introduced ethical rules and commentary using lines from Chicago-location movies and shows. With three of the panelists wearing sunglasses reminiscent of The Blues Brothers to set the stage, the program put a fun spin on illustrating critical legal ethics issues affecting every business lawyer.

The program, moderated by Sanford (“Sandy”) P. Shatz (partner at Wright, Finlay & Zak, LLP), featured helpful insights from A.J. Singleton (general counsel and member of Stoll Keenon Ogden PLLC), Amy Richardson (shareholder at Maynard Nexsen PC and senior lecturing fellow at Duke University), Shawn Garrett (founding attorney of Garrett, PLLC), and Ashley Stasak (associate attorney at Marshall Dennehey, P.C.).

Competency

The program started with a famous line from Home Alone (“You’re what the French call ‘les incompétents’”) to stress that under ABA Model Rule 1.1, “A lawyer shall provide competent representation to a client.” As Stasak put it, “This is not a ‘fake it until you make it’ situation.” If a lawyer is not familiar with a subject area, they are obligated to learn the subject area before providing representation in it. Lawyers need to be honest with themselves about their level of competency. Singleton added that once a lawyer promises a client what can be done, it is hard to back away from it. To avoid getting into such a difficult situation, honesty about level of competency is the key.

Connecting the duty of competence to a hot-button issue, Stasak highlighted two levels of competency in connection with the use of generative artificial intelligence (“AI”): competency in using the AI tool and competency in evaluating the AI-generated content. Shatz and Richardson used real cases to warn the audience of the consequences that can result from unguarded use of AI and citation of fake cases “hallucinated” by generative AI.

Organization as Client

When representing an entity, a lawyer is the steward of the organization itself as a client, according to ABA Model Rule 1.13. With quotes from Eight Men Out and National Lampoon’s Christmas Vacation, the discussion explored the aspects of the rule that guide what a lawyer for an organization must do when they know a person associated with the organization is violating a legal obligation to the organization, or violating a law in a way that is likely to injure the organization. Richardson summed up ABA Model Rule 1.13(b) as the obligation of “reporting up” and ABA Model Rule 1.13(c) as the permissive option of “reporting out.” According to Singleton, seeking attorney representation may help shield such difficult communications with attorney-client privilege.

Richardson additionally noted that sometimes a state may have special rules on who an organizational client is when a lawyer is representing the government.

Dealing with Entity Clients and Their Employees

Relatedly, when representing an entity, the entity’s employees are not a lawyer’s clients unless there are allowable joint representations with all necessary conflict waivers. This should not catch the entity’s constituents off guard. The panel noted this with Clark Griswold’s famous line in National Lampoon’s Christmas Vacation: “Surprised, Eddie? If I woke up tomorrow with my head sewn to the carpet, I wouldn’t be more surprised than I am right now.” Garrett led the discussion of ABA Model Rule 1.13(f), which requires a lawyer to explain the identity of the client when the lawyer knows or reasonably should know that the organization’s interests are adverse to those of the constituents with whom the lawyer is dealing, and the interwoven ethics rules under ABA Model Rule 1.13(g) (which allows a lawyer’s dual representation of both an organization and its constituents) and ABA Model Rule 1.7 (which sets forth the prerequisites for a lawyer to represent a client when a concurrent conflict of interest exists). Garrett shared Singleton’s insights in Singleton’s 2021 co-authored article on how to identify the client in the case of an unformed entity. Singleton emphasized that there are only one or two states that allow a client to be a not-yet-formed entity relying on their respective specific versions of Rule 1.13.

Garrett explained that when a lawyer’s client is an entity, the attorney-client privilege rests with the entity client, rather than the entity’s constituents. The panel also discussed the complexities in tripartite representation—with Stasak using the example of her day job to illustrate tripartite representation involving insurance carrier, policyholder, and attorney.

Attorney-Client Privilege

The program discussed several complex aspects of attorney-client privilege. “The absolute attorney-client privilege protects client’s request for legal advice and their lawyer’s response; it does not necessarily protect the fact,” Shatz noted. Richardson added that, once a client has shared confidential information about a case with ChatGPT, it is hard to maintain attorney-client privilege retroactively later on. Stasak echoed that the shared information is discoverable—as Richardson and Singleton said, “That’s a waiver.” Shatz also reminded the audience that “reply all” in email communications can jeopardize attorney-client privilege.

Confidentiality

The confidentiality obligation of a lawyer under ABA Model Rule 1.6 is fundamental to the legal profession. With a quote from The Untouchables (“What are you prepared to do?”), Singleton invited the audience to think about what lawyers are supposed to do to protect confidentiality as a professional obligation. The panel also discussed various scenarios under ABA Model Rule 1.6(b) where a lawyer may reveal information relating to client representation. Having client consent under ABA Model Rule 1.6(a) can be a safe harbor for revealing information. When a lawyer has to disclose client representation information when changing law firm jobs, using a confidentiality agreement (nondisclosure agreement) can help better protect clients’ confidential information, Singleton said. Singleton further added that, even when a lawyer has to comply with a court order to disclose confidential information, a lawyer still needs to take measures to limit the ways and amount of information to be disclosed—for example, by asking the court whether the disclosure can be done in the judge’s chambers—even when doing so would be to the lawyer’s own disadvantage.

A lawyer’s confidential obligation continues for former clients under ABA Model Rule 1.9. But while Model Rule 1.9 permits using information relating to a former client when it has become generally known, ABA Model Rule 1.6 does not have Model Rule 1.9’s “generally known” exception for current clients. As Singleton put it, “just because something is generally known about your current client” it doesn’t mean you can disclose it.

The program ended with discussions from Singleton and Richardson about candor toward the tribunal under ABA Model Rule 3.3, which is an exception to Model Rule 1.6.

Conclusion

The audience were still sitting in the Chicago meeting room, digesting the familiar yet complicated legal ethics rules regarding competency, organizational clients, attorney-client privilege, and confidentiality, with panelist-presented figures and lines from familiar Chicago movies replaying one after another, when Shatz announced that the show was over.

With the ABA Business Law Section’s spring and fall meetings changing locations each year, will future CLE programs of legal ethics be presented in some other cities’ styles? In this AI era, what other AI-related ethics issues will future CLE panelists enlighten the legal industry about? Whatever the details, the ABA Business Law Section’s Professional Responsibility Committee is sure to find more engaging ways to teach about legal ethics.

To learn more, view the program as on-demand CLE, free for Business Law Section members.

Corporate crises are inevitable. From cyberattacks to whistleblower complaints of executive misconduct, lawyers, both in-house and outside counsel, are usually among the first people pulled in to assist in addressing these crises. Lawyers are often expected not just to answer the legal questions associated with such crises, but also to guide corporate leaders in identifying problems, preserving attorney-client privilege, selecting appropriate resources, and satisfying fiduciary duties, all while maintaining legal and ethical standards throughout the process. The CLE program “When the Alarm Sounds: Boardroom Crisis Management in Real Time,” presented at the 2026 ABA Business Law Section Fall Meeting in Chicago, Illinois, provided practical guidance on governance, privilege and internal investigations, communications strategy, regulatory exposure, and legal and ethical compliance when facing moments of crisis.

This showcase program was moderated by Mac McCoy, a partner at Carlton Fields, P.A. in Tampa, FL, and past chair of the Business Law Section, and featured Margarita Rohaidy Delgado, founder and president of MRD Consulting; Cara Bradley, deputy general counsel of Brooks Automation; Ami N. Wynne, partner at Morgan, Lewis & Bockius; and Forrest J. Deegan, principal consultant at Spark Compliance Consulting, a Diligent brand. Together, these panelists led an interdisciplinary, thought-provoking conversation by walking through three fictional case studies— (1) a cyberattack, (2) a CEO ethics crisis, and (3) a patent and trademark war—and discussing best practices for tackling the issues in each respective scenario.

What Keeps You Up at Night?

Prior to diving into the case studies, the panelists set the stage for the discussion by sharing, from their unique perspectives, the thoughts that consume their minds in moments of crisis. “Do you have a game plan? . . . Do you have a team?” Bradley said, alluding to the need to have the proper resources in place before a crisis arises. Deegan stated that when it comes to a crisis, it is not a matter of how it will happen, but when it will happen. Next, Delgado emphasized concerns surrounding communication strategies and understanding vulnerabilities and communication risks before a crisis. Lastly, Wynne stressed what appeared to be the common, overarching theme shared by all: proper preparation.

Case Study #1: The Cyberattack

When a national healthcare company experiences a ransomware attack that risks compromising patient information, how does counsel respond? It is certain that in-house counsel will be pulled in immediately, but what should their priority be? In these situations, the lawyer’s job is not to slow the process, but instead to impose order on chaos. True to the theme of preparation, to impose such order, it is important for counsel to adhere to the incident response plan—which requires that companies and organizations have an incident response plan in place and ready to be executed.

But having a plan in place is not the only thing that matters. Bradley noted how important it is to determine who the team to carry out this plan will be. That includes considering which internal stakeholders are best equipped to address the situation, and what outside experts are the best fit to support the internal team; combined, they will form the core crisis team. An example of a core crisis team for a cyberattack may include the general counsel and other in-house counsel (as needed), the CEO or other designated executive lead, outside counsel, an IT or other information security lead, a communications professional, a compliance or regulatory lead, and an insurance or risk management lead. Ultimately, it becomes the job of the assembled team to collaborate by carrying out their respective tasks and following the plan in place.

Case Study #2: The CEO Ethics Crisis

Imagine the CEO of a publicly traded company is accused of maintaining a personal relationship with a major vendor, where emails are discovered that evidence a consulting arrangement in exchange for luxury travel and gifts. Although formal charges have yet to be filed, employees and investors are raising important questions. In this situation, it is imperative to address the elephant in the room: accountability. According to Wynne, it is important for the investigation team not just to focus on the policies and procedures in place to address such situations, but to consider the accountability factor, as that is ultimately what can have major implications here.

In scenarios like this, communication plans are also key components of the crisis response, as audiences, both internally and externally, will be waiting for responses. Per Delgado, appropriate disclosures may include acknowledgement of the situation, messaging that an investigation has been initiated, notice that counsel has been retained, and, most importantly, assurance that the company takes this issue seriously and will take appropriate actions based on the findings. In this particular situation, the lawyers assigned to this crisis should evaluate legal liability, regulatory exposure, fiduciary duties, disclosure obligations, employment consequences, insurance coverage, contractual obligations, litigation risk, privilege and waiver, and reputation and stakeholder trust.

Case Study #3: The Patent and Trademark War

A technology company launches a new artificial intelligence platform, and within hours a competitor files a lawsuit alleging patent infringement, trademark confusion, and theft of property concepts. Media outlets publish the story under headlines like “AI Company Accused of Stealing Competitor’s Innovation.”

As a best practice, the public statement that should be made in this situation and related situations is that you do not discuss active litigation in public. Further, it is important to note that anything that is discussed may be used in litigation.

Another best practice in this instance is that, given the high litigation stakes, attorneys need to be involved in approving all messaging, both internally and externally. It is important that attorneys review messaging for accuracy, consistency with public statements, preservation instructions, confidentiality obligations, media response guidance, whistleblower and anti-retaliation issues, and litigation hold language. Deegan shared that in these situations, it is imperative that communications teams have the correct legal contact to avoid delays; this ultimately needs to be addressed and planned for in the applicable crisis management plan.

Key Takeaways

In discussing these crisis scenarios that boards may face, the panel’s most common takeaway was that preparation and timing are key. To be prepared in a timely manner, crisis response plans must address who will lead and who should be informed, how to preserve privilege while gathering facts, how to navigate legal and ethical dilemmas, how to coordinate communications strategies without increasing liability, and how to advise boards through difficult governance decisions. Ultimately, it is important to plan the dive, and dive the plan.

To learn more, view the program as on-demand CLE, free for Business Law Section members.

Jessica Mendelson and Emily J. Stover served as Editors for this publication, Shera Y. Kwak and Aja Nunn served as Assistant Editors, and Rosemary M. Soliz served as Editorial Assistant.

Contributors to this publication include: MacKenna Alvarez, Yoon Cho, Kaveh Dabashi, Madalyn Doucet, David R. Gobel, Matthew L. Honig, Alex Kargher, Lauren Kazen, Nyssa Leonardi, Josh Lopez, Boris Lubarsky, Vanna Mavromatis, Candace Polster, Devonae Robinson, Joshua Salinas, Remy Snead, Nicole Tackabery, and Nicole K. Wong.

Introduction

2025 saw a continuing trend of pending noncompete bills proposed across over 30 states nationwide. Many of the pending bills continue to propose applying limitations around healthcare workers or providing or implementing wage thresholds for certain professionals or low-wage workers. Most recently, Washington state’s chambers of the Legislature approved Engrossed Substitute House Bill (ESHB) 1155, which would prohibit the use of nearly all noncompetes in Washington state. Governor Bob Ferguson signed this bill on March 23, 2026.

Further, though the Federal Trade Commission’s (“FTC”) attempt to impose a nationwide ban on employee noncompete agreements is no more, we have continued to see federal regulatory actions and judicial scrutiny. The FTC issued a request in September 2025 for information on employee noncompete agreements, “to better understand the scope, prevalence, and effects of employer noncompete agreements, as well as to gather information to inform possible future enforcement actions.” Specifically, the FTC requested that “[m]embers of the public including current and former employees restricted by noncompete agreements, and employers facing hiring difficulties due to a rival’s noncompete agreements, are encouraged to share information about the use of noncompete agreements.” Additionally, many courts are continuing to express reluctance in enforcing post-employment restrictive covenants.

In light of these ongoing trends that show no signs of reversing, it is critical that businesses continue to stay current on both federal enforcement trends and state legislative changes. This Trade Secrets and Employee Mobility chapter provides an overview of the key developments for 2025, highlighting the implications and ongoing trends for businesses and practitioners.

First Circuit

In 2025, legislative activity in the First Circuit reflected continued efforts to further limit noncompete agreements broadly (S0302 in Rhode Island) and in specific sectors (healthcare in Rhode Island and New Hampshire, veterinarians in Massachusetts), though all of these attempts ultimately stalled short of passage. See S. 302, 2025 Gen. Assemb., Jan. Sess. (R.I. 2025); S. 703, 2025 Gen. Assemb., Jan. Sess. (R.I. 2025); H.B. 386, 2025 Gen. Ct. (N.H. 2025); S. 1366, 2025 Gen. Ct. (Mass. 2025). The advancement of S. 302 in Rhode Island—which passed the Senate but was never brought up in the House—is a notable attempt to revisit broad noncompete legislation that was previously vetoed by Governor Dan McKee in 2024.

There were also a number of cases out of the First Circuit this year, all from Massachusetts courts interpreting various aspects of the 2018 Massachusetts Noncompetition Agreement Act (MNAA). Massachusetts’ highest court confirmed that non-solicitation agreements are outside the scope of the MNAA. A state trial court upheld an employer’s garden leave clause and provided valuable guidance on how courts will apply the Act. And in two other cases, courts refused to enforce noncompete agreements for failing to comply with the highly technical requirements of the MNAA.

In Miele v. Foundation Medicine, Inc., 250 N.E.3d 294 (Mass. 2025), the Massachusetts Supreme Judicial Court (SJC) ruled that a forfeiture clause triggered by breach of a non‑solicitation agreement is not a “forfeiture for competition agreement” within the scope of the MNAA. Although the Act specifically excludes “covenants not to solicit,” the trial court issued a ruling in favor of the plaintiff-employee, finding the forfeiture provision was unenforceable under the Act. The SJC disagreed and explained that treating a non-solicitation clause differently because it contains a forfeiture mechanism would contradict the MNAA’s express exclusion of covenants not to solicit and render the statute “internally contradictory.”

In Misiaszek v. Korn Ferry, No. 2584CV01766 (Mass. Sup. Ct. July 29, 2025), the Massachusetts Superior Court sided with the employer, finding its garden leave clause enforceable under the MNAA’s requirement that a noncompete be supported by payment during the “entirety of the restricted period” and “except in the event of a breach by the employee [does] not permit the employer to unilaterally discontinue or otherwise fail or refuse to make the payments.” Mass. G. L. c. 149 § 24L(b)(vii). Korn Ferry’s noncompete provision provided that an employee would not compete for a six-month period after their employment ended, “provided that Korn Ferry continues to pay you your then existing base salary during that six-month time period.” The court found this conditional language consistent with the MNAA which “contemplates that an employer need not pay garden leave if it waives ‘the restriction upon post‑employment activities.’” The court also found the employer’s proffered legitimate business interest—the protection of confidential business information—a sufficient and protectable interest that could not be adequately protected by nondisclosure and non-solicit agreements.

In Warren v. Zapata Computing, Inc., 2025 WL 1556040 (D. Mass. June 2, 2025), a Massachusetts federal court held that an employer’s counterclaims based on violation of a noncompete provision failed because there was no evidence to establish that the employee was expressly informed of the right to consult legal counsel prior to signing the agreement. In Anaplan Parent LP v. Brennan, No. 2025-J-0685 (Mass. Sup. C. Oct. 7, 2025), a state court dealt another blow to an employer’s attempt to enforce a noncompete provision for failing to comply with a technicality: the parent company, rather than the subsidiary that directly employed the executive, had signed the agreement. The court imposed a narrow definition of the term “employer” under the MNAA and held the agreement was therefore unenforceable because it was not signed by the employer. Together, these cases illustrate the continued importance for Massachusetts employers to understand and comply with all requirements of the MNAA when drafting and implementing noncompete agreements.

Second Circuit

In 2025, the Second Circuit did not significantly change how courts address noncompete and trade secret litigation. On the legislative side, a New York bill (Senate Bill S4641) was introduced that would prohibit most noncompete agreements if passed and will likely be closely watched in 2026. The Southern District of New York issued two instructive rulings regarding the requisite level of specificity necessary to bring, and maintain, a trade secret action.

First, in Cartiga, LLC v. Aquino, the Court confirmed that the Second Circuit has not required that a trade secret be pled with a particular degree of specificity but must provide enough specificity to put a defendant on notice. No. 24 CIV. 1014, 2025 WL 388804, at *8 (S.D.N.Y. Feb. 4, 2025). In Cartiga, the Court denied defendant’s motion to dismiss plaintiff’s trade secret cause of action for failure to state a claim holding that a “plaintiff cannot get away with nebulous descriptions at the highest level of generality,” but that “‘a DTSA plaintiff has no obligation to reveal its secrets in the Complaint simply to prove that they exist.’” Id. (internal citation omitted). The Court found the plaintiff had sufficiently identified five categories of information which it plausibly alleged were trade secrets including the compilation of client information.

Second, in Hayden v. IBM, the Court granted defendant’s motion for summary judgment holding that plaintiff had failed to define alleged trade secrets with requisite specificity to identify a protectable trade secret. No. 21-CV-2485, 2025 WL 1697021 (S.D.N.Y. June 17, 2025). The Court found that plaintiff was inconsistent when identifying the purported trade secrets, failed to identify the individual elements of the trade secret, and how those components combined to form a trade secret. The Court noted that the numerous documents provided by plaintiff created a “moving target” due to the vague labels and high-level content. The Court concluded that even though this may have been a tactic to protect the trade secret from competitors, this tactic ultimately proved to be fatal to the misappropriation claims.

Third Circuit

On the legislative front, Pennsylvania’s Fair Contracting for Health Care Practitioners Act went into effect on January 1, 2025. The Act generally makes noncompete covenants entered into after the effective date void and unenforceable against “health care practitioners,” as defined by the Act. The Act has exceptions. Most notably, employers may enforce noncompetes if the duration is no more than one year and the employer did not cause the health care practitioner’s dismissal.

While New Jersey legislators continued to push two bills (Senate Bill No. 4385 and Assembly Bill No. 5708) that would ban most noncompete agreements in the state, neither passed before the 2025 legislative session ended. Both bills are expected to be reintroduced during the 2026 legislative session, likely with more momentum and support than in prior years.

Delaware does not have legislation addressing restrictive covenants, so case law continues to shape the landscape. Through its 2024 rulings in Cantor Fitzgerald, L.P. v. Ainslie, 312 A.3d 674 (Del. 2024) and LKQ Corp. v. Rutledge, 337 A.3d 1215 (Del. 2024), the Delaware Supreme Court upheld forfeiture-for-competition clauses and found that because they are not a restraint on trade, they do not need to meet Delaware’s reasonableness standards for enforcing restrictive covenants.

Pointing to the holdings in Ainslie and Rutledge, the plaintiffs in Fortiline, Inc. v. McCall, 341 A.3d 1027 (Del. Ch. 2025) argued that damages for breach of a restrictive covenant are akin to the loss of a supplemental benefit under a forfeiture-for-competition provision, and thus, if the remedy sought is money, rather than injunctive relief, the covenants should not be subject to review for reasonableness. The court rejected this argument. It explained that application of the reasonableness standards hinges “on what the provision demands of the employee, not what the company seeks as a remedy for its breach. If the provision restrains the employee from work, then reasonableness review kicks in. If it does not—if instead, for example, it allows the employer to retain a benefit the employee would otherwise receive—then courts must enforce that term as written.” Id. at 1033. The McCall court held that the plaintiffs were not entitled to any damages because the restrictive covenants were unreasonable and unenforceable.

Additionally, several 2025 decisions highlight enforcement issues that arise when equity or profit incentive agreements contain forfeiture clauses in addition to, and separate from, affirmative restrictions such as noncompetes. For example, in North American Fire Ultimate Holdings, LP v. Doorly, No. 2024-0023-KSJM, 2025 WL 736624 (Del. Ch. Mar. 7, 2025), the for-cause termination of the employee’s employment resulted in the automatic forfeiture of his incentive units. As a result, the Delaware Court of Chancery held that the employer had eliminated the sole consideration for restrictive covenants set forth in the incentive unit agreement, making them unenforceable. Similarly, in Payscale Inc. v. Norman, No. 2025-0118-BWD, 2025 WL 1622341 (Del. Ch. June 9, 2025), the Delaware Court of Chancery held that a noncompete provision set forth in a director-level employee’s incentive equity agreements was unenforceable. The court reasoned that even if the director’s forfeited equity had some value when the parties executed the incentive equity agreements, that consideration could not support the broad 18-month, nationwide noncompete.

Notably, the court in Payscale also declined to blue-pencil the noncompete. The refusal to blue‑pencil is consistent with other recent decisions from Delaware courts.

Fourth Circuit

Over the past year, states in the Fourth Circuit have sought to expand the protections available to employees against restrictive covenants through proposed legislation and case law. For example, the Fourth Circuit has narrowed the employees bound by noncompete agreements by imposing minimum income requirements and near-categorical exemptions for employees in certain fields. District courts similarly expressed reluctance to enforce restrictive covenants, suggesting convergence in legislative and judicial attitudes toward post-employment restrictive covenants.

There were several notable developments relating to state noncompete and non-solicitation laws.

• North Carolina introduced HB 269—the “Workers Freedom and Protection Act”—which would broadly prohibit employers from entering into, requiring, enforcing, or threatening to enforce noncompete agreements, including restrictions on employee mobility between franchise locations, for workers earning less than $75,000 annually.
• South Carolina introduced two bills: HB 3273, which would prohibit noncompete agreements between nonprofits and their employees—nullifying existing covenants for nonprofits with over $1 billion in gross revenue—and HB 4767, which would prohibit noncompete clauses in physician contracts.
• Maryland expanded its restriction on noncompete agreements, rendering them null and void for workers earning 150% or less of the state minimum wage and for veterinary practitioners and technicians. For licensed healthcare workers providing direct patient care who earn $350,000 or less, noncompete provisions are limited to one year in duration and a 10-mile radius from the primary place of employment.
• Effective July 1, 2025, Virginia expanded its ban on noncompetes with low-wage employees to include workers who earn less than the Commonwealth’s average weekly wage or who are entitled to overtime under the FLSA. See Va. Code. Ann. § 40.1-28.7:8.

There are a couple of interesting cases that have been decided in the Fourth Circuit in 2025. In Allegis Grp., Inc., et al. v. Bero, No. 23-2023, 2025 WL 2141298 (4th Cir. July 29, 2025), the Fourth Circuit affirmed summary judgment in favor of former employee Christopher Bero. The court held that Bero did not breach his non-solicitation agreement because his post-employment recruiting activities did not relate to the specific business area he had serviced while employed. Id. at *3. As a result, the employers could not show that his conduct fell within the scope of the contractual restriction. The court also rejected the nondisclosure claim, finding that Bero merely sent confidential information to himself and that there was no evidence he disclosed the information to any third party. Id. at *4. Without proof of external disclosure or misuse, the nondisclosure agreement could not support liability.

In Sysco Machinery Corp. v DCS USA Corp., 143 F.4th 222 (4th Cir. 2025), the Court articulated the pleading standards for trade secret claims under both the Defend Trade Secrets Act and North Carolina’s Trade Secrets Protection Act. The Court emphasized that a plaintiff must plausibly allege the existence of a protectable trade secret and facts showing misappropriation. Id. at 228. It further held that depositing technical drawings with the U.S. Copyright Office extinguished any trade secret protection in those materials. Id. at 229. The Court reiterated that misappropriation requires the acquisition, disclosure, or use of a trade secret by improper means or without the owner’s consent. Id. at 229.

Fifth Circuit

The Fifth Circuit saw some minor developments in the last year, with a few cases of note. In Worldvue Connect Global, L.L.C. v. Szuch, 155 F.4th 472 (5th Cir. 2025), the Fifth Circuit addressed the scope of a noncompete and non-solicitation provision that arose out of the sale of a business, and held that they covered both independent contractors employed by a third-party agency and employees who physically resided outside of the restricted area but provided services within the restricted area.

The provision at issue provided, in relevant part, that the defendants would not solicit its customers or “recruit, solicit, induct or attempt to induce, directly or indirectly, any of the employees or independent contractors of [Plaintiff] or any of its direct or indirect subsidiaries, to terminate their employment or contractual relationship with [Plaintiff] or any such subsidiary . . . .” The agreement also provided that the defendants could not engage in competitive business in the restricted area for one year.

At issue in the case was whether this provision applied to employees and contractors of the plaintiff who physically lived out of the restricted area but provided services to clients of the plaintiff in the restricted area, and whether it applied to customer service agents who provided services to the plaintiff in the restricted area but were employed by a third-party staffing company.

The defendants argued that the parties agreed that they would not solicit or compete “in” the restricted area, and that the provision should, therefore, not apply to remote workers who live and work outside the restricted area. According to the defendants, interpreting the provision to cover workers who did not live in the restricted area but provided services in that area would erase the contractual restricted area limitation.

The majority of the Fifth Circuit rejected that argument both because the plain language of the agreement confirmed this interpretation and because the evidence showed that the scope of the restriction was reasonable given the nature of the plaintiff’s business. The majority also rejected the argument that the non-solicitation provision did not apply to customer service agents who provided services to the plaintiff but were employed by a third-party staffing company. As the court noted, agreeing with the defendants’ argument “would exclude the customer service agents from the solicitation agreement entirely despite those agents performing essential work for the [plaintiff] in the operation of its business.” This would create an “unreasonable construction.”

Hon. James L. Dennis issued a dissenting opinion, but it did not deal with the substance of these conclusions. Instead, Circuit Judge Dennis took issue with a threshold point—whether there was a basis for injunctive relief at all. He felt that the District Court failed to assess this issue and improperly relied on a contractual provision which permitted the issuance of an injunction in the event the noncompete or non-solicitation provisions were violated.

In the trade secrete theft space, the Fifth Circuit once again confirmed that demonstrating the existence of a trade secret is essential to suing for theft of a trade secret. In DeWolff, Boberg & Associates Incorporated v. Pethick, 133 F.4th 448 (5th Cir. 2025), the Fifth Circuit affirmed an order granting summary judgment for the defendant as to a misappropriation claim due to Plaintiff’s failure to identify with specificity what information in its Salesforce Database was non-public, or distinguish between public and non-public information in that database. It also found that there was no evidence that the defendants used or disclosed any trade secrets, which also supported affirming the trial court’s ruling.

Finally, at the state court level, there was an interesting decision about the importance of drafting an enforceable noncompete agreement. In Allen & Smith Insurance Agency Inc. v. Merrill, No. 2023-CA-00468-COA, — So.3d –, 2025 WL 1441926 (Miss. Ct. App. May 20, 2025), the Court of Appeals of Mississippi affirmed a trial court ruling that struck the noncompete and non-solicitation provisions in an agreement between an insurance agent and their former employer on the grounds that they were so vague as to be unenforceable. Among other issues, the Court found the provisions internally inconsistent such that the defendant was placed in a “very uncertain position” when trying to determine their scope. As the Court of Appeals noted, “[t]he agreement’s terms should have been clear, unambiguous, and reasonable from the onset.” That the provisions at issue in this decision were not rendered them unreasonable and unenforceable.

Sixth Circuit

The past few years, the Sixth Circuit has reversed several district courts that disposed of trade secret claims as time-barred on summary judgment, allowing those claims to survive. In 2025, the Sixth Circuit ended its streak. In Cincom Systems, Inc. v. Labware, Inc., the Court agreed with the district court that the plaintiff’s former employee’s social media activity put the plaintiff on “inquiry notice” of misappropriation, thus starting the countdown for filing its complaint, which expired by the time of filing. No. 24-3726, 2025 WL 2742573, at *8 (6th Cir. Sept. 26, 2025). The limitations period begins running either when “the misappropriation is discovered or by the exercise of reasonable diligence should have been discovered.” Kehoe Component Sales Inc. v. Best Lighting Products, Inc., 796 F.3d 576, 582 (6th Cir. 2015). These decisions discuss when misappropriation “should” be discovered with reasonable diligence.

Let’s recap the previous decisions. In B&P Littleford v. Prescott Mach., LLC, the district court held that “B&P’s claim accrued no later than 2012 and was therefore time-barred,” citing a 2012 customer tip as when B&P should have discovered the misappropriation, and it granted summary judgment over the claim filed in 2018. No. 20-1449, 2021 WL 3732313, at *6 (6th Cir. Aug. 24, 2021). However, the Sixth Circuit reversed. Id. at *7. After the tip in 2012, B&P had inquired whether Prescott showed B&P’s drawings to other customers, and it submitted a criminal complaint to the FBI. Id. at *8. Although those efforts did not successfully yield additional evidence, the Sixth Circuit held that “a jury could find that B&P satisfied its obligation of conducting a reasonable investigation.” Id. In Campfield v. Safelite Group, Inc., the district court granted summary judgment that Safelite’s trade secret counterclaim was time-barred; Campfield had sent Safelite a letter in 2010 (outside the limitations period), listing materials to support Campfield’s Lanham Act claim, which Safelite would later allege had been misappropriated. 91 F.4th 401, 415 (6th Cir. 2024). According to the district court, the 2010 letter should have triggered a further investigation into Campfield’s alleged misappropriation. Id. The Sixth Circuit reversed, agreeing with Safelite that “[n]othing in the letter suggested that the information at Campfield’s disposal had been stolen,” and Safelite was not obligated to further investigate any potential misappropriation. Id. Last, in Metron Nutraceuticals, LLC v. Cook, the district court granted summary judgment that Metron’s claim was time-barred, reasoning that because Metron had filed a lawsuit in 2016 against Thomas (another co-defendant), Metron was obligated “to investigate further” at that time. No. 23-3596, 2024 WL 3877388, at *12 (6th Cir. 2024). The Sixth Circuit reversed, noting that the prior lawsuit against Thomas involved different operative facts, and that “the district court did not explain what investigative steps Metron should have taken” to discover the misappropriation at that time. Id. at *13.

We turn to 2025. In Cincom Systems, Inc. v. LabWare, Inc., the Sixth Circuit affirmed a district court’s award of summary judgment that trade secret misappropriation was time-barred. No. 24‑3726, 2025 WL 2742573 (6th Cir. 2025). In 2014, a former disgruntled Cincom employee posted on his personal blog that he was both joining defendant LabWare and working on “Smalltalk [virtual machine] work.” Id. at *4. This raised red flags among Cincom personnel, saying “there was no way [LabWare] could have legally obtained a copy of the underlying source code” for that technology. Id. at *5. However, a repost of the former employee’s post provided additional information suggesting to Cincom that “it was far more likely that LabWare would be using an open-source Smalltalk variant,” and Cincom decided to wait until “we have evidence that he and/or his company are in violation” before following the lead. Id. In 2014, Cincom did nothing further to investigate, such as reaching out to the defendant or another entity suspected of having pertinent information. Id. Instead, it was not until 2019 when Cincom conducted a “rapid, successful investigation” to gather evidence of misappropriation. Id. at *8. The district court time-barred the 2019 claim, finding that Cincom was on “inquiry notice” based on the blog post in 2014. Id. at *4. On appeal, the Sixth Circuit rejected Cincom’s attempts to rely on all three cases discussed above (B&P Littleford, Campfield, and Metron), distinguished them, and agreed that the claims were time-barred. Id. at *7. The Court discussed all the facts at Cincom’s disposal in 2014, including the social media posts and other public information about LabWare’s technology. Id. at *6. The Court explained, “If Cincom had made at least some showing of chasing down these leads, then it would at least arguably have behaved as a reasonably prudent person should.” Id. *8. Cincom was therefore on “inquiry notice,” and if it had investigated (even if unsuccessfully, like B&P Littleford), it could have avoided summary judgment. See id.

Seventh Circuit

There were no relevant authorities in this circuit over the past year.

Eighth Circuit

Case law in the Eighth Circuit remains largely unchanged with respect to matters regarding employee mobility, restrictive covenants, and trade secrets. That said, there are a few notable points of discussion:

On March 4, 2025, Arkansas Governor Sarah Huckabee Sanders signed into law Senate Bill 139, now Act 232 (the “Act”), which amended the state’s noncompete statute to provide that noncompete covenants that “restrict the right of a physician to practice within the physician’s scope of practice” are now void. The Act became effective 90 days after the conclusion of the current legislative session in mid-July 2025.

A few interesting cases have also come out of the Eight Circuit in the past year. In Choreo, LLC v. Kevin Lors et al., No. 25-1706, 2026 WL 82841, (8th Cir. Jan. 12, 2026), the Eighth Circuit vacated a preliminary injunction that had been granted to Choreo, LLC, against its former employee, Kevin Lors, and his new employer, Compound Planning. Choreo had sought the injunction based on allegations that Lors violated a non-solicitation clause by encouraging former clients to switch to his new employer. The district court granted the injunction, finding irreparable harm based on Choreo’s further loss of customer relationships. On appeal, the Eighth Circuit emphasized that mere allegations of competition or potential loss of clients were insufficient to establish irreparable harm without clear evidence that such harm could not be adequately remedied by monetary damages. As a result, the court vacated the injunction, reinforcing the need for a strong showing of harm to obtain a preliminary injunction.

In Ellingson Drainage, Inc. v. Kippen, No. 3:22-cv-189, 2025 U.S. Dist. LEXIS 265935, No. 3:22-cv-189 (D.N.D. Sep. 30, 2025), the U.S. District Court addressed a claim under the Defend Trade Secrets Act (DTSA), where Ellingson Drainage alleged that Kippen, a former employee, and Landmark, Kippen’s new employer, misappropriated its trade secrets. Ellingson contended that Kippen took valuable, proprietary information, such as client lists and pricing data. The court examined whether Kippen’s actions constituted misappropriation of such information. Ultimately, the court found that Ellingson Drainage had not taken reasonable measures to keep the information secret. While Ellingson Drainage had directed its employees that the information was confidential, evidence showed that employees sometimes left the supposedly confidential information with Ellingson Drainage’s customers, or in file cabinets that were accessible by anyone. As such, Kippen and Landmark were entitled to summary judgment on the DTSA claim.

Finally, Zest Labs sued Walmart in 2018 for allegedly stealing its Zest Fresh technology, which tracks produce freshness from farms to stores. Zest Labs Inc. et al. v. Walmart Inc., Case No. 4:18-cv-00500 (E.D. Ark.). Following a retrial in May 2025, a jury in Arkansas federal court found that Walmart owed Zest Labs more than $222 million. The jury awarded Zest Labs 72.7 million in compensatory damages and $150 million in punitive damages, finding that Walmart had misused its trade secrets after Zest shared its technology for improving food preservation with Walmart. After the jury award, the parties agreed to a confidential settlement to resolve all issues between them.

Ninth Circuit

AB 692

California recently adopted new legislation impacting employee mobility, namely AB 692, or California Business & Professions Code Section 16608. This statute, which went into effect on January 1, 2026, prohibits employers from including “in any employment contract, or to require a worker to execute as a condition of employment or a work relationship a contract that includes, specified contract terms, including a term that requires the worker to pay an employer, training provider, or debt collector for a debt if the worker’s employment or work relationship with a specific employer terminates.” The law creates a private right of action, allowing affected workers to bring claims on behalf of themselves and similarly situated individuals. Remedies include minimum damages of $5,000 per affected worker, injunctive relief, and recovery of attorneys’ fees and costs.

While AB 692 restricts certain repayment obligations, it includes several important exceptions. First, loan repayment assistance and forgiveness programs, which include contracts “entered into under any loan repayment assistance program or loan forgiveness program provided by a federal, state, or local governmental agency,” are excluded from the law. Second, agreements for “the repayment of the cost of tuition for a transferable credential” are excluded provided all of the following conditions are met: (1) the agreement is offered “separately from any contract for employment”; (2) “the contract does not require obtaining the transferable credential as a condition of employment” (3) the repayment amount is specified in advance, not exceeding “the cost to the employer of the transferable credential received by the worker”; (4) the agreement provides for a “prorated repayment amount during any required employment period that is proportional to the total repayment amount and the length of the required employment period and does not require an accelerated payment schedule if the worker separates from the employment”; and (5) repayment is not required if the worker is terminated, “except if the worker is terminated for misconduct.” Third, contracts “related to enrollment in an apprenticeship program approved by the Division of Apprenticeship Standards” are excluded from the prohibition. Fourth, contracts for discretionary or unearned monetary payments “at the outset of employment that is not tied to specific job performance” are excluded provided all of the following conditions are met: (1) repayment terms are in a “separate agreement from the primary employment contract”; (2) the employee is told of the right to consult an attorney and given at least five business days to do so prior to executing the repayment obligation agreement; (3) repayment is “not subject to interest accrual,” prorated based on remaining retention period, up to two years, and may be deferred until “the end of a fully served retention period”; and (4) repayment may only be required if separation is voluntary or due to employee misconduct. Finally, contracts relating to the “lease, financing, or purchase of residential property, including, but not limited to, a contract pursuant to the California Residential Mortgage Lending Act” are excluded from the statute.

Oregon Bureau of Labor & Industries updates to ORS 653.295

Effective January 1, 2026, Oregon’s minimum compensation required to enforce employee noncompetition agreements increased to an annual gross salary and commissions threshold of $119,541. This change narrows the group of employees who may be subject to enforceable noncompetition agreements while leaving intact Oregon’s existing statutory requirements for enforcement of a noncompete. As a result, employers should reassess current and future noncompetition agreements to ensure compliance with the heightened compensation threshold.

Quintara Biosciences, Inc. v. Ruifeng Biztech, Inc., 149 F.4th 1081 (9th Cir. 2025)

In Quintara Biosciences, Inc. v. Ruifeng Biztech, Inc., the Ninth Circuit clarified the level of detail plaintiffs must provide about their trade secrets in order to survive dismissal in the early stages of federal trade secrets litigation. 149 F.4th 1081 (9th Cir. 2025). There, Quintara Biosciences, a California-based DNA sequencing company, filed suit against its competitor also based in California, Ruifeng Biztech, for misappropriation of trade secrets under the federal Defend Trade Secrets Act (DTSA), 18 U.S. Code § 1836. Quintara alleged that Ruifeng misappropriated several trade secrets, including but not limited to customer and vendor databases, marketing plans, and computer software code. From the beginning of discovery, Ruifeng argued that Quintara must specify its trade secrets with “reasonable particularity” under the California Uniform Trade Secret Act (“CUTSA”). After several attempts to force Quintara to provide more detail about its trade secrets, Ruifeng eventually moved to strike Quintara’s trade secrets claims under Federal Rule of Civil Procedure 12(f), which the District Court for the Northern District of California granted for nine of them.

The Ninth Circuit, however, reversed, and clarified that unlike for CUTSA, plaintiffs bringing claims under the federal statute need only identify their trade secrets with “sufficient particularity” at the outset of litigation. Further, the question of whether or not a plaintiff has defined their trade secrets with sufficient particularity is a factual one that should be resolved at trial or through summary judgment, not through motions to strike. According to the Ninth Circuit, the District Court should have allowed Quintara “to refine its identifications through discovery” instead of “functionally dismiss[ing]” nine of its trade secret claims so early on. The District Court’s failure to do so was an abuse of discretion.

David v. Freedom Vans LLC, 4 Wash. 3d 242, 562 P.3d 351 (Wash. 2025)

David v. Freedom Vans LLC has recently given greater clarity to Washington statute RCW 49.62, which—somewhat paradoxically—both prohibits employers from restricting low wage employees from moonlighting at other jobs to supplement their income, but also preserves employees’ common law duty of loyalty to their employers. Low wage employees are considered those making less than twice the minimum hourly wage (which, as of 2025, is $33.32 per hour or $69,305 per year).

In David v. Freedom Vans LLC, Freedom Vans employees were subject to in-term noncompete agreements prohibiting them from “directly or indirectly engaging in any business that competes” with Freedom Vans during their employment. Two former employees sued Freedom Vans. In compliance with these noncompete agreements, they had forgone “side jobs” that would have supplemented their income while working for Freedom Vans. Although the lower courts found that Freedom Vans could lawfully prohibit low wage employees from engaging in “any kind of assistance” to competitors due to the exception for the common law duty of loyalty under RCW 49.62.070, the Washington Supreme Court demanded a narrower interpretation of the duty of loyalty exception. The Washington Supreme Court held that a blanket prohibition against such “side jobs” with an employer’s competitors would unreasonably broaden employees’ duty of loyalty and would undermine the legislature’s intent to permit low wage employees to supplement their income. The Washington Supreme Court remanded the case. The Court advised that, on a case-by-case basis, anti-moonlighting and duty of loyalty provisions must be narrowly drafted and will be strictly construed when applicable to low wage employees in Washington. This case sets the precedent for Washington companies to re-evaluate, and potentially narrow, their “anti-moonlighting” or noncompete provisions in their employment agreements or company handbooks. In the wake of David v. Freedom Vans LLC, counsel for the plaintiff employees have filed new lawsuits against Amazon, Alaska Airlines and Costco to similarly challenge the companies’ restrictions on their workers.

Tenth Circuit

Litigation Updates

In 2024, Colorado enacted a law strengthening protections for employees subject to training repayment agreement provisions (“TRAPs”). Similar restrictions are increasingly being adopted nationwide, and noncompliance can result in significant exposure, including government enforcement actions and private litigation. State attorneys general have been actively enforcing these laws. More recently, in November 2025, Colorado Attorney General Phil Weiser settled a lawsuit against PetSmart LLC for $225,000 and secured an agreement to stop enforcing TRAPs with groomers. In July 2025, the attorneys general of California, Colorado, and Nevada reached a multi-state settlement with HCA Health Care, Inc., which paid approximately $2.9 million and agreed to additional remedial measures over allegedly unlawful training repayment agreements.

In 2025, courts in the Tenth Circuit underscored that plaintiffs must clearly identify trade secrets before seeking judicial relief. In Double Eagle Alloys, Inc. v. Hooper, 134 F.4th 1078 (10th Cir. 2025), the U.S Court of Appeals for the Tenth Circuit affirmed summary judgment for the defendants after the plaintiff broadly claimed that an employee’s notes and more than 2,600 downloaded files were trade secrets. The plaintiff failed to show that the information was protectable, did not demonstrate reasonable efforts to maintain secrecy, and could not overcome evidence that the defendants independently developed similar specifications or that much of the material was publicly available. Similarly, in Applied Predictive Technologies Inc. v. MarketDial Inc., Case No. 2:19-CV-00496 (D. Utah Mar. 25, 2025), a Utah federal court sharply rebuked Applied Predictive Technologies for pursuing trade secret claims without evidence of an identifiable secret, ultimately awarding $2.8 million in attorneys’ fees to the defendants. Both cases highlight that trade secret claims must be clearly defined, supported by evidence, and protected through reasonable secrecy measures—or risk dismissal and potential sanctions.

Developments in the Healthcare Space

In 2025, Colorado and Utah joined a growing list of states limiting the use of restrictive covenants in the healthcare space.

In March 2025, Utah passed SB-228, which prohibits healthcare services platforms—defined as any “program, system, or application through which a health care worker may accept a shift to perform a health care service or role, as an independent contractor, at a health care facility”—from requiring a healthcare worker to enter into a noncompete agreement. The law defines healthcare workers broadly as any “individual who provides or delivers a health care service, or assists in the provision or delivery of a health care service, including a service for which no license or certification” is required.

In June 2025, Colorado passed SB-25-083, which prohibits covenants—such as noncompetes and patient non-solicitation provisions—that restrict the practice of medicine, advanced practice registered nursing, or dentistry, regardless of whether the practitioner is a highly compensated worker. The law also expressly permits healthcare providers departing their practice to disclose to their patients (a) that they will continue to practice medicine; (b) their new professional contact information; and (c) patients’ right to choose a healthcare provider.

Other Developments

In Kansas, the Governor signed SB 241, which amends the Kansas Restraint of Trade Act. SB 241 took effect on July 1, 2025. The amendment establishes a presumption that certain customer and employee non-solicitation agreements are enforceable. Covered circumstances include employee non-solicitation or non-recruitment provisions that either (1) seek to protect confidential or trade secret information, customer or supplier relationships, goodwill, or loyalty, OR (2) do not extend beyond two years following the end of employment. The presumption also extends to customer non-solicitation provisions that do not continue for more than two years. A presumption of enforceability also now exists for agreements in “which an owner agrees to provide prior notice of the owner’s intent to terminate, sell or otherwise dispose of such owner’s ownership interest in the business entity.” SB 241 further mandates judicial modification of overbroad restrictive covenants. Kansas courts are now required to “modify the covenant, enforce the covenant as modified and grant only the relief reasonably necessary to protect such interests.”

In Wyoming, the Governor signed Senate File 107, now Enrolled Act No. 87 (the “Act”), which renders void any covenant not to compete that restricts a person’s right to receive compensation for the performance of labor. The Act applies to contracts entered into on or after the effective date of July 1, 2025. The Act contains language broad enough to make most noncompete covenants with workers void regardless of a worker’s status as an employee or an independent contractor, or the type of agreement the covenant may be found in. Also included in the Act is a restriction on training repayment agreements and expense relocation agreements that do not satisfy statutory limitations. The Act contains several common exemptions, including agreements with “executive and management personnel” and with “employees who constitute professional staff to executive and management personnel,” although these terms are not defined. It also permits noncompete provisions in connection with the purchase or sale of a business or its assets, and allows covenants to the extent they protect trade secrets. These exceptions, however, do not extend to any agreements “between physicians that [restrict] the right of a physician to practice medicine.”

Eleventh Circuit

Over the past year, practitioners in the Eleventh Circuit saw significant developments that changed the contours of restrictive covenant enforcement and trade secret litigation.

The Federal Trade Commission dismissed its appeals in Properties of the Villages v. FTC (11th Cir.) and Ryan, LLC v. FTC (5th Cir.), stepping away from a nationwide noncompete ban. The agency’s leadership has indicated it instead plans to rely on case‑by‑case enforcement to challenge unjustified or overly broad noncompetes, particularly for lower‑wage workers, with the goal of pushing firms to use only narrowly tailored restrictions tied to legitimate business interests.

Florida’s Legislature moved in the opposite direction of many states by enacting the Contracts Honoring Opportunity, Investment, Confidentiality, and Economic Growth (CHOICE) Act, effective July 1, 2025. The CHOICE Act supplements Fla. Stat. § 542.335 and creates a parallel, employer‑friendly enforcement track for covered employees (generally those earning at least twice the county’s annual mean wage). It codifies robust tools for noncompetition and garden‑leave arrangements, including a strong presumption of enforceability, mandatory issuance of preliminary injunctions absent a clear‑and‑convincing showing by the employee, a seven‑day review period, and continued salary and benefits during garden leave. It also authorizes notice and garden‑leave periods up to four years. With states around the country continuing to restrict or ban post‑employment noncompetes, the CHOICE Act positions Florida as one of the most employer‑friendly jurisdictions for restrictive covenants.

In Alabama Aircraft Indus., Inc. v. Boeing Co., 133 F.4th 1238 (11th Cir. 2025), the court reversed the district court’s dismissal of a trade secret misappropriation claim under the Missouri Trade Secrets Act, which the court applied pursuant to the parties’ contractual choice-of-law provision rather than Alabama law. The court held that although a contractual limitation‑of‑liability provision may bar most forms of damages, it does not categorically foreclose an unjust‑enrichment remedy where that recovery would not duplicate contract damages.

In NetRoadshow, Inc. v. Carrandi, No. 25-10388, 2025 WL 2435411 (11th Cir. Aug. 25, 2025) (unpublished), the court vacated the dismissal of an employee’s counterclaim under California Business and Professions Code section 16600.5. The court held that a Georgia choice‑of‑law clause limited to “this Agreement” did not automatically bar a statutory tort claim arising from a source outside the contract, and therefore did not prevent the employee from invoking California’s noncompete statute. On remand, the district court must apply Georgia’s choice‑of‑law precedent and its public‑policy exception to determine which state’s law governs the statutory claim. For multistate employers confronting the extraterritorial reach of California’s noncompete ban, the decision cautions that a contractual choice‑of‑law provision alone may not resolve statutory counterclaims, and although unpublished, it still signals how the Eleventh Circuit may approach conflicts‑of‑law issues involving foreign noncompete statutes.

At the state level, the Georgia Court of Appeals in All States AG Parts, LLC v. Herzig, 374 Ga. App. 389, 913 S.E.2d 26 (2025), reaffirmed that noncompetes restricting work “in any capacity” are facially overbroad and are unlikely to be salvaged through blue‑penciling.

Finally, in Rotech Healthcare, Inc. v. Carmichael, No. 6:23‑cv‑2338‑JA‑RMN, 2025 WL 2879775 (M.D. Fla. Oct. 9, 2025), the court held that an employee’s act of forwarding the employer’s detailed referral‑source lists and sales notes to his personal email shortly before joining a competitor constituted misappropriation under both the Defend Trade Secrets Act and the Florida Uniform Trade Secrets Act, even without evidence of post‑departure use or disclosure.

DC Circuit

There were no relevant authorities in this circuit over the past year.

Modern frameworks for corporate liability assume that corporate actions ultimately reflect human choices, employing concepts such as intent, authority, foreseeability, and control. But the emergence of agentic artificial intelligence challenges these frameworks by introducing new, nonhuman “decision-makers” into corporate environments, raising difficult questions about who is at fault when something goes wrong.

This article discusses a recent Ninth Circuit decision involving an AI agent. It also explores the challenges of applying existing liability frameworks when AI agents cause harm, and practical steps businesses using AI tools can take to mitigate the risk of causing such harm.

On August 4, 2026, in Amazon.com Services, LLC v. Perplexity AI, Inc. (No. 26-1444, 2026 WL 2237587), the Ninth Circuit noted that an AI agent at issue in the case “is a tool, not a person for statutory purposes.” Although that distinction may seem self-evident, how courts will analyze liability in the context of agentic AI is not.

In Amazon v. Perplexity, the Ninth Circuit grappled with this conundrum in a first-of-its-kind case. Amazon alleged that the AI company Perplexity’s AI agent accessed Amazon’s computer systems without authorization. The AI agent, called the Assistant, is a feature of Perplexity’s internet browser that can perform tasks such as online shopping via an Amazon customer’s account.

In the lawsuit, Amazon claimed that Perplexity’s Assistant accessed its online store in violation of the Computer Fraud and Abuse Act (“CFAA”) and the California Comprehensive Computer Data Access and Fraud Act (“CDAFA”). Amazon also requested a preliminary injunction enjoining Perplexity from allowing the Assistant to access Amazon’s computer systems. The district court granted the preliminary injunction.

Perplexity appealed, and the Ninth Circuit vacated the preliminary injunction, reasoning that Amazon was unlikely to succeed on the merits because the Assistant did not technically “access” Amazon’s computer systems. Notably, the court acknowledged there is little to no case law on liability and agentic AI, and it sought to limit the implications of its decision, writing:

We do not establish a new legal regime governing agentic AI. We do not address whether in other contexts, including tort claims, Perplexity can avoid liability for the Assistant’s actions. . . . The legal understanding of agentic AI will doubtless change as AI technology grows increasingly sophisticated.

The court’s decision raises a question: What is the legal regime governing agentic AI?

The emergence of AI agents presents real and present challenges in both civil and criminal contexts. AI agents—essentially tools that use AI models to execute complex series of steps—can “make decisions” about how to most effectively perform a task. But who is responsible for those decisions? And what if intent is an element of a crime or tort allegedly committed by an AI agent?

Consider civil fraud. If an employee acting in good faith prompts an AI agent to develop and execute a marketing campaign, but the campaign contains false representations inserted by the AI agent, and it is later discovered that several customers relied on the campaign’s false representations when entering into new contracts with the company, can the company be liable for fraud? Can the employee? The AI developer? How can anyone be liable for fraud without an intent to mislead?

Similarly, imagine a CEO who prompts an AI agent to research a competitor, leaves the agent running overnight, and returns in the morning to find that the agent hacked into the competitor’s servers and copied confidential business plans onto the CEO’s computer. Did the CEO hack the competitor?

These scenarios may sound like science fiction, but they are not. OpenAI, for example, recently announced it is reassessing its security and monitoring standards after AI agents being tested for cybersecurity capabilities escaped their testing environment and hacked into another AI company’s systems without any human instruction to do so. These scenarios may also leave organizations wondering how they can protect themselves from AI agents acting in unintended ways.

Even without guidance from courts or legislators, companies using AI agents can take steps now to mitigate the risk of AI-related harm. These steps typically require collaboration between legal and IT departments, and they include the following:

• Set parameters on AI agents’ authority: Organizations should think carefully before permitting AI agents to communicate externally. Granting this authority increases the risk of an AI agent misleading third parties.
• Establish human-in-the-loop processes: AI agents need to be managed. This management should include requiring human approval before an agent executes sensitive steps, such as accessing files in a shared drive.
• Keep records of AI agents’ activities: Implement systems to track the tasks agents perform. Knowing how agents are used can help identify risks before they materialize.
• Implement an AI usage policy: Organizations should provide clear guidance to employees about what AI agents may or may not be used for.
• Deter “shadow AI”: Shadow AI is the unapproved use of AI tools within an organization, often by employees using their own personal accounts. While there are technical tools that can govern this use, good management practices can also help identify and deter shadow AI.

As the Ninth Circuit noted in Amazon v. Perplexity, the law on agentic AI will continue to evolve. In the meantime, organizations that use AI agents can and should take proactive steps to mitigate the risk of an AI-related incident while still capturing the efficiencies AI agents can offer.

Starting a nonprofit organization can be deeply rewarding, not only for its founders but also for society at large. However, just like starting a for-profit company, forming a nonprofit demands careful planning and due diligence. Counsel for nonprofit founders must not only establish the entity under applicable state law but also structure the organization and its governing documents to support the client’s intended activities and, where applicable, qualify for federal and state corporate tax exemption. This article will attempt to demystify the formation process and provide an overview of the steps involved in creating a nonprofit corporation, from incorporation to obtaining an EIN, drafting corporate documents, and applying for recognition of federal tax-exempt status.

Nonprofits come in all shapes and sizes and can be formed in any state, the District of Columbia (“DC”), and all territories of the United States. For the sake of brevity, this article will focus primarily on the process of forming a DC nonprofit corporation, though the incorporation process is similar in most other jurisdictions.

1. Identify the Nonprofit’s Mission and Organizational Structure

Before preparing the nonprofit’s initial corporate documents, counsel should work with the client to identify the nonprofit’s proposed activities, anticipated funding sources, governance structure, and intended federal tax-exempt classification. At a minimum, counsel should understand the following:

• what activities the nonprofit will conduct
• who will benefit from those activities
• where the nonprofit will operate
• how the nonprofit will be funded
• whether the nonprofit will have statutory members (i.e., individuals or entities who have some level of control and voting power within the nonprofit, such as electing the nonprofit’s directors and officers or the ability to approve a merger or dissolution)
• whether the nonprofit will solicit contributions from the public
• whether the nonprofit will charge for goods or services

These are not merely business planning considerations. They directly inform the nonprofit’s appropriate entity structure, type of federal tax exemption, state and local tax obligations, licensing requirements, and charitable solicitation registration requirements. I recommend advising the client to develop a comprehensive business plan that covers the above and other information about the nonprofit, its business, and finances. Doing this work early on can save a lot of time and expense later in the formation process.

Additionally, counsel should discuss the composition of the nonprofit’s initial board of directors with the client. A nonprofit corporation should have at least three directors (but preferably five or more) who will manage and oversee the nonprofit’s affairs. In many jurisdictions, the initial directors must be listed in the nonprofit’s articles of incorporation (more on articles of incorporation below), so it’s important to identify the initial directors as early in the process as possible. At this time, the client also should be thinking about who will serve as the nonprofit’s initial corporate officers (e.g., president, secretary, treasurer). The officers are charged with carrying out the nonprofit’s day-to-day activities, so those individuals should be genuinely and enthusiastically dedicated to the nonprofit’s mission.

2. Prepare and File Articles of Incorporation, and Obtain an EIN

After those preliminary items are nailed down, the next step is to prepare and file the articles of incorporation. Articles of incorporation state the name of the nonprofit, its initial directors, its office address, its registered agent information, whether the corporation will have statutory members, and other basic information. To qualify for federal tax exemption, some nonprofits also must include certain IRS-required language in their articles of incorporation. For example, a nonprofit that is organized as a 501(c)(3) entity must include a purposes clause and a dissolution clause that complies with the federal Internal Revenue Code’s (and corresponding U.S. Treasury Regulations’) requirements. The articles of incorporation become public record once they are accepted by the jurisdiction of incorporation, so I generally recommend keeping them brief and concise, only disclosing the information required by law and needed to qualify for recognition of federal tax exemption.

Once the articles of incorporation have been drafted, they must be submitted, along with a state filing fee, to the corporation regulator in the jurisdiction of incorporation. In DC, that is the DC Department of Licensing and Consumer Protection. When the articles of incorporation are approved, the DC Department of Licensing and Consumer Protection (or other applicable corporation regulator) will issue a certificate of incorporation recognizing the nonprofit as an officially formed corporation. Some states also have a publication requirement, whereby the nonprofit must publish certain information ora copy of the articles of incorporation in a newspaper of regular circulation in the jurisdiction of incorporation. Be sure to reference the relevant jurisdiction’s nonprofit corporation statutes to determine all requirements for incorporation.

Immediately following incorporation, counsel should obtain a federal employer identification number (“EIN”) from the IRS on the nonprofit’s behalf. This can be done by filing an application (called the IRS Form SS-4) online, which usually takes ten to twenty minutes to complete. The nonprofit’s EIN serves as its tax identifier with the IRS and is required to open a bank account in the nonprofit’s name, register for state-level taxes, and apply for recognition of federal tax-exempt status, among other things, so it is important to obtain an EIN early in the formation process.

At this time, if the nonprofit intends to operate as a 501(c)(4) organization, counsel should prepare and file an IRS Form 8976 to notify the IRS that the nonprofit will operate as a 501(c)(4) entity. Note that this filing must be made within sixty days of the nonprofit’s incorporation or financial penalties may apply.

3. Draft Bylaws, Policies, and Organizational Meeting Documents

After incorporation, counsel should prepare bylaws and governance policies for the nonprofit.

The bylaws describe in detail the nonprofit’s internal structure and operating procedures. This includes rules relating to director and officer elections and removals, meetings, board committees and membership, and other matters related to the conduct of the nonprofit’s business and affairs. Counsel should ensure that the bylaws are consistent with the articles of incorporation and the relevant jurisdiction’s nonprofit corporation statutes.

A set of governance policies also should be prepared. An effective set of governance policies enables the nonprofit to follow best practices and comply with applicable laws and regulations while providing clear guidance for navigating typical nonprofit transactions. Standard governance policies include confidentiality, anti-discrimination and harassment, joint venture, whistleblower protection, executive compensation, and conflict of interest policies. Certain nonprofits may require additional policies based on their planned activities, such as a scholarship policy for a nonprofit that will operate a scholarship program or a foreign transactions due diligence policy for a nonprofit that will provide foreign aid or otherwise transfer goods or funds across borders.

Many jurisdictions, including DC, require that the board of directors hold an initial board meeting after incorporation. The first board meeting is called the “organizational meeting.” At the organizational meeting, the board will adopt the bylaws and policies and take care of other initial housekeeping matters and corporate formalities, such as adopting a fiscal year, electing officers, authorizing the opening of a bank account, and ratifying any corporate acts taken prior to the meeting. Often this will be done via unanimous written consent—a document stating the relevant corporate resolutions and signed by all directors—in lieu of holding a meeting. Counsel should prepare draft sample organizational meeting minutes or a unanimous written consent to guide the client through its first board actions.

4. Apply for Recognition of Federal Tax-Exempt Status

Once the nonprofit is incorporated, has adopted bylaws and governance policies, and has held its organizational meeting, the next step is to prepare and file a federal tax exemption application. There are four federal tax exemption applications: IRS Form 1023, IRS Form 1023-EZ, IRS Form 1024, and IRS Form 1024-A. The appropriate application depends on the (anticipated) size of the nonprofit and type of federal tax exemption sought. For example, the IRS Form 1024-A is used to apply for recognition of 501(c)(4) status, while the IRS Form 1023 is used to apply for recognition of 501(c)(3) status. The IRS Form 1023-EZ also is used to apply for recognition of 501(c)(3) status but is reserved for smaller, less complex nonprofits.

The federal tax exemption applications (except for the IRS Form 1023-EZ) are comprehensive and require counsel to explain the nonprofit’s business, finances, and affairs in detail. This includes a detailed description of the nonprofit’s planned activities and financial projections for the first few years of operation. It is important to be as detailed as possible in the federal tax exemption application to maximize the nonprofit’s chances of approval and minimize the chances of questions and requests for additional information.

The federal tax exemption application is filed, along with a mandatory user fee, online with the IRS. While it is hard to gauge exactly how long it will take the IRS to process and approve an application, currently, the general rule of thumb is to expect to wait six to eight months. When the application is approved, the nonprofit will receive a favorable “determination letter” from the IRS that confirms the recognition of its tax-exempt status. While the application is pending, the nonprofit may begin operating, but it is important to remind the client that it must be clear with the public, and especially potential donors, that the nonprofit’s federal tax exemption application is pending with the IRS and, for would-be 501(c)(3) organizations, that donations are not yet tax deductible as charitable contributions. If the application is filed within twenty-seven months of the nonprofit’s incorporation, when the IRS does approve the nonprofit’s application, it will recognize the nonprofit’s exemption retroactively to the date the nonprofit was incorporated, and charitable contributions made to the nonprofit prior to receiving its determination letter then become tax deductible for the donor.

5. Register for DC Taxes and Apply for a Basic Business License and for Charitable Solicitation Purposes, if Necessary

As a corporation, the nonprofit is subject to state and local taxes. Each jurisdiction has different taxes (e.g., income, franchise, sales, use, real and personal property) and tax reporting requirements. In DC, if the nonprofit has employees, it will need to withhold DC-level income tax from wages, consistent with current DC withholding requirements. Generally, the nonprofit must register with the relevant tax authorities in each jurisdiction where it is conducting business or has employees (including remote employees). In DC, corporations must register as a new business with the DC Office of Tax and Revenue (“DC OTR”). To register as a new business, the nonprofit must complete and file Form FR-500 with the DC OTR.

It is important to remember, and to remind the client, that federal tax exemption does not necessarily provide exemption from state and local taxes. Each jurisdiction has different rules for qualifying for, applying for, and maintaining state and local tax exemptions. In many cases, state and local tax exemption is available only after the IRS has issued a favorable determination letter. In DC, certain 501(c)(3) organizations may qualify for exemption from DC’s income and franchise, sales and use, and personal property taxes. To apply for these tax exemptions, counsel should prepare and file Form FR-164 with the DC OTR.

In DC, any entity that provides goods or services for compensation must obtain a Basic Business License from the DC Department of Licensing and Consumer Protection. Accordingly, if the nonprofit’s activities include the sale of goods or services (even at a discounted rate), the nonprofit will need to obtain a Basic Business License.

Finally, most jurisdictions require charitable organizations to register with the appropriate state authority (typically, the state attorney general’s office) if the nonprofit will solicit donations from individuals or businesses located within that jurisdiction. The purpose of these “charitable solicitation registrations” is to protect the public from deceptive or misleading fundraising activities. In DC, charitable organizations intending to solicit donations must apply for a Basic Business License with the DC Department of Licensing and Consumer Protection under the “Charitable Solicitation” category. To maintain its charitable solicitation registration, the nonprofit must file annual reports, which typically include a copy of the nonprofit’s most recently filed IRS Form 990 (annual information return). The definition of “solicitation” varies with each jurisdiction. In several states, simply having a “donate” button on the nonprofit’s website may trigger registration, depending on the circumstances. Counsel should determine if and where the nonprofit must register before the client begins soliciting contributions. The rules and requirements applicable to charitable solicitations vary by jurisdiction, and counsel should not assume that registration is required only where the nonprofit is incorporated or maintains a physical office. Many third-party corporate compliance vendors offer charitable solicitation registration services to nonprofits, so if you are unsure of the requirements in any jurisdiction, the safest option is to refer the client to one of those vendors.

Conclusion

For business attorneys, nonprofit formations should be viewed as more than merely an entity formation exercise. Effective counsel weighs the business considerations against potential risks to ensure that the nonprofit is structured in such a way to accomplish the nonprofit’s mission under the client’s desired structure while qualifying for federal (and, if desired, state) corporate income tax exemption. Each step of the formation process is interconnected. Decisions made at the outset can affect the organization’s governance, fundraising activities, eligibility for tax exemption, and corporate compliance obligations for years to come.

For attorneys who do not regularly handle nonprofit matters, engaging nonprofit counsel—or obtaining specialized advice on nonprofit tax, governance, and charitable solicitation issues—can be particularly valuable where the client’s activities, funding arrangements, or intended tax-exempt classification raise issues beyond routine corporate formation.

For more information, contact the author at [email protected].

Cross-border infrastructure acquisitions have traditionally been driven by commercial expansion, operational efficiencies, and financial return; infrastructure assets have long attracted strategic investors because of their relatively stable cash flows, inflation-linked revenues, long concession periods, and portfolio diversification benefits. Nevertheless, global infrastructure mergers and acquisitions (“M&A”) activity slowed during 2025. Excluding the proposed acquisition of Hutchison Ports, global infrastructure deal value declined from approximately US$28 billion in 2024 to US$22 billion in 2025, while the number of completed transactions fell from fifty-one to forty.^[1] Although financing conditions and broader macroeconomic uncertainty contributed to this decline, investor appetite for strategically significant infrastructure assets has remained resilient.

Within the infrastructure sector, ports occupy a distinctive position. They are no longer viewed merely as transportation assets but increasingly as critical infrastructure connecting global supply chains, logistics networks, industrial development, and national security interests. The disruptions experienced in recent years—including the COVID-19 pandemic, the Red Sea crisis, and renewed tensions surrounding the Strait of Hormuz—have further highlighted the strategic importance of geographically diversified port networks.

This article argues that the recent geopolitical developments suggest that strategic resilience is becoming an increasingly important investment consideration, particularly when you look at the instability surrounding the Strait of Hormuz. These kinds of developments are influencing not only where operators based in the Persian Gulf (“Gulf”) invest but also how cross-border acquisitions are evaluated, structured, and negotiated. While the legal framework governing M&A transactions remains fundamentally unchanged, geopolitical considerations appear to be playing an increasingly prominent role throughout the transaction life cycle, influencing valuation, due diligence, transaction structuring, and contractual risk allocation.

Why Strategic Infrastructure Is Different from Other Assets

When M&A involves infrastructure, it does not fundamentally alter the legal mechanics of an acquisition. Share purchase agreements (“SPAs”), due diligence, valuation methodologies, and transaction structuring remain the core tools of every cross-border transaction. However, the nature of the underlying asset significantly influences how those tools are applied. In this respect, acquisitions involving strategic infrastructure—and ports in particular—differ from acquisitions of ordinary commercial businesses.

Unlike many corporate assets, ports perform a dual function. They are commercial enterprises generating revenue for their owners, but they also constitute critical infrastructure supporting international trade, supply chains, energy security, and, in some jurisdictions, national security. Their operation is therefore closely connected with public policy objectives and is frequently governed by concession agreements, public-private partnership frameworks, or sector-specific regulatory regimes.

This means that the acquisition of a port is rarely assessed solely through the lens of projected cash flows or expected operational synergies. Because governments and regulators increasingly view ports as assets whose ownership may affect broader public interests, foreign investment approvals, sector-specific regulation, and ongoing governmental oversight often assume greater significance than in transactions involving nonstrategic assets.

The strategic nature of ports also influences how buyers evaluate value creation. While conventional valuation techniques remain unchanged, the commercial attractiveness of a port may extend beyond its standalone financial performance. Its geographic location, connectivity to global logistics networks, access to alternative trade corridors, and contribution to a diversified infrastructure portfolio may all enhance its strategic value. In this sense, a port may represent not merely an operating business but a long-term strategic position within an investor’s broader network.

The United States provides a useful illustration of how national security considerations have increasingly influenced the regulatory framework governing foreign acquisitions of strategic infrastructure. Although the Committee on Foreign Investment in the United States (“CFIUS”) has long reviewed foreign acquisitions presenting national security concerns, its jurisdiction was expanded under the Foreign Investment Risk Review Modernization Act of 2018 (“FIRRMA”) to cover certain noncontrolling investments in U.S. businesses involved in critical infrastructure, critical technologies, and sensitive personal data.^[2] This expansion reflects the growing recognition that national security concerns may arise not only from the acquisition of control over strategic assets but also from certain minority investments and associated governance rights.

The political sensitivity of port acquisitions was evident well before FIRRMA, however. In 2006, Dubai Ports World’s proposed acquisition of the U.S. port operations of British firm P&O generated substantial congressional opposition and public debate over national security, notwithstanding the transaction’s prior review by CFIUS.^[3] The controversy illustrates that acquisitions of strategically important infrastructure may face political and national security considerations extending beyond conventional competition law analysis.

Investment Strategies’ Evolution

The first question an investment committee asks is not “How should the SPA be drafted?” but rather, “Why are we acquiring this port?” The answer to that question has evolved significantly over time. In the early 2000s, the response would most likely have focused on increased container throughput, higher revenues, greater EBITDA, economies of scale, and market expansion. In short, the primary objective was growth. Port acquisitions were fundamentally about generating greater financial returns.

A decade later, the investment rationale became more sophisticated. Port operators increasingly evolved into integrated logistics providers, expanding beyond terminals into inland depots, rail connections, warehouses, logistics parks, and other value-added services. The strategic objective was no longer simply to own ports, but to control larger segments of the supply chain and create integrated logistics platforms.

Today, however, investment committees ask different questions. What happens if a major trade corridor is disrupted? What if sanctions affect a key market? Is the existing portfolio overly concentrated in one region? How resilient is the operator’s global network? Growth remains important, but resilience has become an equally significant investment objective. The legal mechanics of the acquisition have not fundamentally changed; the commercial rationale has.

For transactional lawyers, this evolution is significant. We continue to negotiate the same legal documents—SPAs, shareholder agreements, and transaction documents—but we do so in support of a different business strategy. Transactional lawyers are not merely document drafters. They must understand why their client or company is acquiring a particular asset because that commercial objective inevitably influences the priorities of the transaction. A client acquiring a port to strengthen network resilience will not necessarily negotiate different legal concepts, but it may place considerably greater emphasis on governance rights, concession stability, expansion opportunities, and long-term regulatory certainty than a buyer motivated solely by short-term financial returns. The role of the transactional lawyer is therefore no longer limited to documenting the acquisition. It increasingly requires an understanding of the commercial, regulatory, and geopolitical considerations that shape the investment itself. In strategic infrastructure transactions, legal execution and business strategy are no longer separate disciplines—they are increasingly intertwined.

The Gulf’s Outbound Diversification Strategy

Recent transaction activity suggests that Gulf-based port operators are increasingly pursuing geographic diversification as part of their long-term investment strategy. Although few transactions expressly identify geopolitical risk as their principal driver, several acquisitions and investments indicate an emphasis on expanding beyond traditional regional trade corridors. Examples include DP World’s reported interest in acquiring a stake in Associated British Ports in the United Kingdom,^[4] DP World’s continued investments in Senegal and India,^[5] and AD Ports Group’s acquisition of MBS Logistics.^[6] More recently, DP World also announced plans to develop a port and logistics hub in Fujairah on the United Arab Emirates’ east coast.^[7] While the project serves multiple commercial objectives, its location outside the Strait of Hormuz also illustrates the growing strategic importance of geographic diversification and supply-chain resilience in infrastructure investment decisions.

Rather than viewing these transactions in isolation, they may be understood as part of a broader effort to strengthen portfolio resilience. For operators with significant exposure to trade routes affected by geopolitical tensions, investments in geographically diverse jurisdictions may reduce concentration risk while expanding access to new markets and supply chains. In this respect, transaction activity itself may provide a more meaningful indicator of evolving investment priorities than public statements accompanying individual acquisitions.

Implications for M&A Practice

Valuation

Traditional infrastructure valuations continue to focus primarily on projected cash flows, concession durations, growth prospects, and the regulatory environment in which the target operates. However, strategic buyers may increasingly assess an acquisition through the broader lens of portfolio resilience. For a Gulf-based port operator whose existing assets are concentrated within a particular maritime corridor, acquiring a port in another jurisdiction may generate strategic value beyond the target’s stand-alone financial performance.

The strategic importance of ports is also evolving beyond their traditional role as stand-alone maritime assets. This broader strategic perspective may also influence valuation. While established valuation methodologies such as discounted cash flow and comparable transactions remain unchanged, acquirers may attribute additional strategic value to assets that strengthen portfolio resilience, expand logistics connectivity, or provide access to alternative trade corridors. Consequently, a target’s contribution to an integrated logistics network may justify a strategic premium beyond its stand-alone operating performance. Thus, geopolitical diversification as well as an integrated logistics network may influence strategic premium that a particular buyer is willing to pay because the acquisition contributes to a more balanced portfolio and reduces concentration risk.

Beyond the Traditional Due Diligence

Legal due diligence traditionally focuses on the target’s assets, contracts, permits, litigation, regulatory compliance, and liabilities. Acquisitions motivated by strategic diversification, however, may require an additional layer of commercial analysis.

The relevant question is no longer confined to whether the target represents a legally and commercially attractive investment. Acquirers may also consider whether the transaction achieves its broader strategic objective of reducing geographic concentration risk and enhancing network resilience. Due diligence therefore extends beyond identifying legal risks within the target itself to evaluating how the acquisition complements the acquirer’s existing portfolio.

Foreign Investment Screening

An increasingly important consideration in cross-border infrastructure M&A is the expansion of foreign direct investment (“FDI”) screening regimes. This is actually a direct consequence of geopolitics. Traditionally, M&A analysis focused primarily on the identity of the investor and competition law considerations. Increasingly, however, regulators also examine the nature of the target itself. Infrastructure assets performing critical supply chain, logistics, or public functions—including ports—may attract enhanced regulatory scrutiny regardless of whether the acquirer is considered a low-risk investor.

This development has important implications for transaction execution. Regulatory approvals under FDI regimes must be factored into transaction timetables, conditions precedent, and long-stop dates, and parties may also negotiate the allocation of regulatory risk if approvals are delayed, conditioned, or refused. The commercial agreement remains central, but the SPA must also address the allocation of regulatory and national security risk, particularly where the target operates critical infrastructure.

Aligning Governance with Strategic Objectives

From a transactional lawyer’s perspective, we can say that strategy determines structure. This becomes especially crucial where a project is developed and operated with multiple partners. Mechanisms such as reserved matters, board composition, business plan approvals, capital commitments, and exit provisions have always been integral components of shareholder agreements and joint venture arrangements. However, where the strategic objective extends beyond financial returns to include portfolio resilience and long-term network diversification, greater emphasis may be placed on governance rights that facilitate those objectives.

For example, investors may seek stronger protections to ensure that strategically important expansion projects—such as the construction of additional berths, logistics parks, inland terminals, or rail connections—cannot be blocked by a joint venture partner. Similarly, shareholders may negotiate mandatory capital contribution obligations, agreed capital expenditure programs, or other funding mechanisms to ensure that future expansion cannot be frustrated by a shareholder’s refusal to finance the business. Business plans may incorporate long-term diversification projects, logistics integration, and capacity expansion as strategic priorities rather than purely operational objectives. Deadlock mechanisms may also have greater importance where disagreements over expansion or strategic investment could undermine the long-term purpose of the acquisition. Likewise, parties may attach greater significance to reserved matters relating to the disposal of strategic land, amendments to concession agreements, changes to the business model, or the surrender of concession rights. The legal tools themselves remain familiar; what changes is the strategic purpose they are intended to serve.

Transaction Structuring and Risk Allocation

Geopolitical uncertainty may also influence the manner in which transactions themselves are initially structured. Rather than pursuing immediate full acquisitions, parties may favor phased investments, joint ventures, minority investments, or staged capital commitments that preserve strategic flexibility while facilitating expansion into new jurisdictions.

An emerging structural response is the pairing of port operators with sovereign co-investors, whether their own state’s fund or another Gulf Cooperation Council (“GCC”) sovereign wealth fund, rather than operators pursuing acquisitions on a stand-alone basis. This model—operator as strategic and operational lead, sovereign wealth fund as capital partner—allows portfolio diversification to be pursued without concentrating balance-sheet risk in any single jurisdiction, while also potentially easing the path through target-state FDI screening, given the increasing scrutiny that sovereign-controlled acquirers face in certain jurisdictions. It further reflects a broader shift already visible across the region, where GCC sovereign wealth funds increasingly negotiate co-investment rights and direct deal access rather than passive allocations.

Approaches to outbound capital deployment vary across GCC port operators. Some pursue acquisitions primarily through internally generated cash flows, prioritizing balance-sheet control and execution speed, while others increasingly structure transactions alongside sovereign co-investors to share capital exposure and broaden deal capacity. Neither approach is inherently superior; the choice reflects the country’s preference and priorities, as well as each operator’s balance-sheet strength, risk appetite, and strategic priorities at a given point in its growth trajectory.

Similarly, established contractual protections may receive greater scrutiny during negotiations. Material adverse change (“MAC”) clauses provide a useful example. In acquisitions of existing port operators, where the target company already holds the relevant concession, parties may negotiate whether the commercial consequences of future geopolitical developments—such as sanctions, disruption of key trade routes, significant increases in operating costs, or other material adverse effects on the target’s business—should fall within the agreed definition of a MAC or instead remain with the buyer as part of ordinary market risk. The significance of this negotiation extends beyond a traditional no-MAC condition to closing. Where geopolitical risks are addressed through representations and warranties, the agreed allocation of risk may also have implications during the post-closing indemnity period, subject to the agreed survival periods and the indemnification regime under the SPA. More broadly, sanctions-related representations, interim period covenants, and conditions precedent may also be tailored to reflect the increased importance of geopolitical considerations. The evolution lies not in the creation of new legal concepts, but in the increasing significance attached to existing mechanisms for allocating commercial risk.

Conclusion

Whether current geopolitical tensions persist or gradually ease, recent developments demonstrate that geographic diversification has become an increasingly important strategic consideration in infrastructure acquisitions. Buyers may therefore evaluate potential targets not only on the basis of their stand-alone financial performance but also on the extent to which an acquisition enhances the resilience and geographic balance of their wider portfolio.

As geopolitical considerations become more deeply embedded in investment decision-making and structuring the deal, they are also likely to receive greater attention throughout the transaction process. Valuation, due diligence, transaction structuring, and contractual risk allocation may increasingly reflect various objectives extending beyond the target itself.

For M&A practitioners, the challenge is no longer confined to executing transactions efficiently. It also involves advising clients and companies on how geopolitical developments influence investment strategy and the legal execution of cross-border acquisitions. In this respect, port M&A activity offers a compelling illustration of the growing intersection of infrastructure investment, geopolitics, and corporate law. It demonstrates that the legal toolkit available to M&A lawyers has not fundamentally changed: What has changed is the commercial environment in which that toolkit operates.

1. McKinsey & Co., Travel, Logistics, and Infrastructure: A Fragile Reset Paves Way for M&A Momentum (Feb. 13, 2026). ↑

2. Press Release, U.S. Department of the Treasury, Treasury Releases Final Regulations to Reform National Security Reviews for Certain Foreign Investments and Other Transactions in the United States (Jan. 13, 2020). ↑

3. National Security Implications of the Dubai Ports World Deal to Take Over Management of U.S. Ports: Hearing Before the H. Comm, on Armed Servs., 109th Cong. (2006). ↑

4. Pramod Kumar, DP World Evaluates Stake in Associated British Ports, Arabian Gulf Bus. Insight (Apr. 9, 2026). ↑

5. Press Release, DP World, DP World to Launch $2.5bn Logistics Infrastructure Investment in 2025 (May 20, 2025); see also Press Release, DP World, DP World Pledges $5 bn Infrastructure Investment in India (Oct. 30, 2025). ↑

6. AD Ports Grp., AD Ports Group Further Consolidates Its Global Logistics Platform with the Acquisition of MBS Logistics (May 18, 2026). ↑

7. Nicolas Parasie, Andrew England & Alice Hancock, Dubai Plans New Port to Bypass Strait of Hormuz, Fin. Times (July 13, 2026). ↑