AI State Regulatory Frontiers: Predictive, Generative, and Agentic Risk

In this episode of Regulatory Oversight, co-host Ashley Taylor, co-leader of Troutman Pepper Locke’s State Attorneys General team, kicks off a multipart series on artificial intelligence (AI) with guests Gurkan Ay and Andrew Coles of Resolution Economics. They unpack what people really mean by “AI” today and why it is critical for risk, compliance, and legal exposure to distinguish among the three primary “flavors” of AI: predictive, generative, and agentic. In practical terms, they explain how predictive tools that score, rank, and classify individuals rely on historical data, how generative AI enables natural-language interaction but introduces risks like hallucinations, and how emerging agentic AI can autonomously plan and execute complex, multistep workflows, creating new governance challenges.

The conversation then turns to how existing legal frameworks are being applied to these technologies, and how regulators are beginning to grapple with different AI use cases without a one-size-fits-all rule set. The guests discuss whether AI truly creates new categories of legal risk or primarily amplifies existing ones through scale, speed, and accessibility, and they highlight the growing role of “regulation by litigation” as courts and enforcers apply long-standing laws to new tools. They close with practical themes: organizations must understand their specific AI use cases, align them with existing legal and consumer expectations, and build defensible, consistent governance and compliance programs to manage legal and operational risk.