Artificial Intelligence

Our AI Practice Group supports clients across a wide range of matters, including:

• AI Governance and Risk Management: We advise on the design and implementation of AI governance frameworks, including enterprise-wide use policies, model risk oversight structures, and board-level accountability mechanisms. This includes developing model inventory systems, human oversight protocols, algorithmic impact assessments, and internal review processes aligned with both current best practices and anticipated regulatory requirements.
• Regulatory and Compliance: The global regulatory landscape for AI is evolving rapidly and unevenly. Our team monitors and advises on AI-specific legislation across jurisdictions, including sector-specific frameworks from financial and healthcare regulators, and emerging federal and state-level requirements in the U.S. We represent clients in interactions with regulators and help build compliance programs adaptable to regulatory developments across multiple jurisdictions.
• Data Privacy and Cybersecurity: We counsel on the full lifecycle of training data—from collection and consent frameworks through cross-border transfer mechanisms and retention obligations—including questions of lawful basis, data minimization, and individual rights in the context of model training. We also advise on cybersecurity obligations specific to AI systems, including incident response planning and protection of model integrity.
• Intellectual Property: Our team advises on the ownership and protectability of AI-generated outputs, strategies for protecting proprietary models and training methodologies, and the mitigation of infringement risk associated with training data inputs and model outputs. We help clients navigate evolving case law while developing practical strategies to protect their AI-related intellectual property.
• Commercial and Technology Transactions: Our transactional team advises on the full range of commercial agreements involving AI technologies, including vendor agreements, licensing arrangements for proprietary models, service level agreements, and collaboration agreements for joint development. We focus particularly on risk allocation—addressing responsibility for model performance, liability for outputs, indemnification for IP and regulatory claims, and the treatment of data rights and model ownership upon termination.
• Litigation and Investigations: Our litigation team represents clients across the full spectrum of AI-related contentious matters, including claims of algorithmic bias, disputes arising from system failures, regulatory investigations, and internal investigations involving misuse of AI tools. We also advise on the admissibility of AI inputs and outputs in litigation and the discovery-related challenges that arise when AI systems are involved in the processing of potentially relevant information.
• Employment and Workplace Considerations: We advise employers on the lawful deployment of AI-powered hiring tools, compliance with emerging bias audit legislation, employee monitoring technologies, workplace policies governing generative AI use, and the broader workforce implications of AI-driven automation.

Our Practice Group serves clients across industries where AI is driving both transformation and legal complexity, including financial services and fintech (algorithmic trading, credit underwriting, fraud detection, regulatory technology), healthcare (clinical decision support, diagnostic AI, drug discovery, protected health information), technology and SaaS (AI product development, deployment, and commercialization), media and entertainment (generative AI’s impact on content creation, licensing, and creator rights), and industrial and logistics (autonomous systems, predictive maintenance, supply chain optimization).

Unlike firms that treat AI as a niche specialty, DarrowEverett embeds AI acumen within the full breadth of our established practice areas—ensuring that every engagement benefits from attorneys who understand the technology, the regulatory environment, the commercial context, and the litigation landscape. When a client’s AI initiative implicates privacy, IP, and vendor contracting simultaneously, our attorneys work together seamlessly rather than handing matters from one silo to the next.

We bring a pragmatic, business-oriented perspective to every engagement. Our clients are not seeking counsel to slow innovation but to enable it responsibly, and our goal is to provide clear, actionable guidance that allows organizations to deploy AI systems that are legally sound, commercially viable, and strategically aligned. We invest continuously in monitoring legislative developments and tracking enforcement trends, ensuring our advice reflects the most current understanding of a rapidly evolving legal landscape.

Our attorneys actively track and analyze key judicial decisions shaping how AI is treated by courts nationwide, including:

• United States v. Heppner (2026)
  The case addresses whether communications between a client and a large language model are protected by attorney-client privilege or the work product doctrine.
• Warner v. Gilbarco, Inc. (2026)
  This case examines the impact of a pro se litigant’s disclosures to a large language model and whether such use constitutes a waiver.
• Nippon Life Insurance Company of America v. OpenAI Foundation and OpenAI Group PBC (N.D. Ill. 2026)
  This high-profile dispute concerning allegations that AI-generated pleadings caused substantial legal costs highlights risks associated with unsupervised AI use in litigation.

These and other developments inform our guidance to clients on responsible and strategic AI adoption.