Asset Managers and AI Integration: Legal and Regulatory Essentials

This CLE course will examine how asset managers use AI, from portfolio analysis and regulatory filing preparation to client communications. The panelists will explain how AI tools create SEC compliance and enforcement risks under anti-fraud and fiduciary duty theories, including Rule 204-2, Regulation S-P, and Rule 17a-4 exposures. AI washing and hushing, third-party vendor oversight, cybersecurity, data privacy, material non-public information (MNPI), privilege, IP protections, and litigation exposure will also be addressed. Attendees will learn practical AI governance, oversight, and disclosure strategies to support defensible, risk-conscious AI deployment.

AI is transforming personal and commercial interactions, and the wealth management sector has quickly integrated it, outpacing most other sectors. Asset managers use AI for portfolio performance analysis, research, compliance monitoring, regulatory filing preparation, and client communications, along with broader commercial functions.

Although the SEC has withdrawn its predictive data analytics proposal, it will continue evaluating and enforcing wrongful AI activities under fiduciary duty of care principles. The SEC has already brought AI washing enforcement actions where companies overstated or mischaracterized AI use in investor-facing materials under anti-fraud standards. AI hushing—the omission or deemphasis of AI-related dependencies—poses comparable enforcement risk. This program will explore these vulnerabilities and how stakeholders can mitigate enforcement and litigation risk.

To reduce regulatory scrutiny and enforcement risk, asset managers must conduct appropriate diligence when selecting, engaging, and overseeing AI providers and employee AI use. Investor disclosures and AI oversight should be tailored to actual use. During this webcast, the faculty will examine common asset manager AI applications and highlight where SEC obligations and risks arise, including with SEC Rule 204-2, Regulation S-P, Rule 17a-4, and fiduciary duty expectations. Because AI tools may gather, store, and use MNPI without an asset manager's awareness, understanding these data practices and documenting safeguards is critical. The panel will also address third-party vendor vetting and oversight.

Beyond SEC requirements, even basic AI use can expose asset managers to data privacy and cybersecurity risks, including meeting recordings and cross-border data storage. These vulnerabilities may trigger state-specific actions, federal enforcement risk, third-party data obligations, breach and cybersecurity requirements, and jurisdictional concerns.

AI-generated call and meeting transcripts may create statutory recordkeeping duties and discoverable materials in civil and regulatory matters. Entering confidential information into AI tools can also risk IP disclosure, privilege waiver, and MNPI dissemination. This authoritative panel will explain these threats and how asset managers can frame AI audits to support tailored governance, oversight, and disclosures.

Listen as our authoritative panel examines asset managers' use of AI, including third-party vendor use, related state and federal enforcement risks, and private litigation exposure. Attendees will gain integration and governance strategies to help asset managers mitigate legal risk through more thoughtful, purposeful AI deployment.