This article is related to a Showcase CLE program titled “AI in the Trenches and on the Bench: A Business Law Toolkit for In-House, Firm, and Courtroom” that took place at the American Bar Association Business Law Section’s 2026 Spring Meeting. All Showcase CLE programs were recorded live and will be available for on-demand credit, free for Business Law Section members.
Artificial intelligence has rapidly evolved from a transformative tool to an essential component of legal practice across in-house counsel offices, law firms, and courtrooms. The AI adoption rate among US attorneys has surged in the last few years. As AI continues to reshape the legal profession, understanding the technology, mitigating risks, and ensuring compliant implementation have become critical competencies for business lawyers.
Generative artificial intelligence (“GenAI”) is a type of AI that can create new content, such as text, images, music, audio, and videos, using machine learning to learn patterns from data and then generate new content based on those patterns. Large language models (“LLMs”) represent one category of AI tools that power many legal applications. Agentic AI represents a paradigm shift toward AI systems designed for autonomous operation, as these systems perceive their environment, reason, make decisions, plan, and act to achieve complex goals with minimal human oversight, sharply contrasting with reactive systems like most generative AI, which only respond to user inputs.
The potential risks of generative AI include “hallucinations” (inaccurate or nonsensical outputs), training data bias resulting in biased outputs, privacy and security risks, and unfair competition, trade secret and intellectual property claims. The US National Institute of Standards and Technology (“NIST”) AI Risk Management Framework Playbook discusses a wide variety of other risks, such as environmental impacts on ecosystems from high resource utilization, potential for large-scale misinformation dissemination, and issues with relying on untraceable data. Beyond technical risks, practitioners must also contend with organizational challenges, including unauthorized “shadow AI” use by employees and compliance with evolving regulatory frameworks.
Ethical considerations require legal practitioners to balance innovation with professional responsibility across multiple dimensions. The duty of competence demands that lawyers understand the capabilities and limitations of AI tools they employ, while communication obligations require transparency with clients about AI use in their matters. Confidentiality concerns arise when sensitive client data is processed through third-party AI platforms, particularly when terms of service remain ambiguous about data retention and use. The duty of candor to tribunals has taken on new significance as courts grapple with AI-generated hallucinations, exemplified by high-profile sanctions in cases where lawyers submitted fabricated citations. Supervisory duties extend to ensuring that junior attorneys, paralegals, and staff use AI tools appropriately and in compliance with firm policies.
Courts have responded with divergent approaches: Some have issued standing orders prohibiting AI use in court filings entirely, with potential sanctions ranging from striking pleadings to contempt citations and case dismissal, while others have declined to adopt special AI rules, instead emphasizing that reliance on AI will not excuse otherwise sanctionable conduct. These varied judicial responses reflect ongoing uncertainty about how to balance technological advancement with the integrity of legal proceedings.
Despite these risks and varied judicial approaches, AI tools offer significant potential for enhancing legal practice when used responsibly. Use cases range from chambers research and case management to in-house contract review, legal research, document drafting, and litigation support at law firms of all sizes.
However, realizing these benefits requires robust governance frameworks. Effective risk mitigation begins with comprehensive internal AI policies that specify permitted tools, authorized tasks, and clear consequences for noncompliance. Contracts with AI vendors must address intellectual property ownership, data privacy protections, security standards, and indemnification provisions.
Given the rapid pace of technological change and regulatory development, organizations should establish regular review cycles to update policies and ensure continued alignment with legal requirements. Supervision protocols must ensure that AI outputs receive appropriate human review, while periodic audits can identify unauthorized use, assess compliance with established policies, and evaluate whether AI tools are delivering intended benefits without introducing unacceptable risks.
By combining clear policies, contractual safeguards, active supervision, and systematic auditing, legal organizations can harness AI’s capabilities while maintaining professional standards and protecting client interests.
