The AI Drop
Unlock the future of artificial intelligence with The AI Drop, a podcast dedicated to delivering cutting-edge insights on how AI is transforming industries worldwide. Each episode features expert interviews and actionable strategies to help you harness AI, drive business value, and navigate evolving legal challenges. Fresh drops every week so you never miss a beat.
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In this episode of The AI Drop, Jason Stanley, Head of Applied AI Research at ServiceNow, returns for another discussion with host Anna Gressel on one of the most pressing challenges in AI governance: how to oversee AI systems that continue to adapt after deployment. Together, they explore what adaptive and self-improving AI means for enterprise risk and governance.
He explains why an AI system can excel at one task yet fail at a slightly reworded version of it, and why critical governance controls must sit beyond an agent's ability to modify them, even if those safeguards may not hold indefinitely.
Jason and Anna also discuss how contracts can transform voluntary standards into binding obligations more quickly than new regulation, and why effective oversight must extend to how AI systems evolve at runtime.
For legal, risk, and technology leaders alike, this conversation gives insight on the governance questions likely to dominate 2027.
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The most effective AI governance programs don't slow innovation down. They create the guardrails, visibility, and trust needed to scale AI responsibly and confidently.
In Part 2 of this conversation, Anna Gressel welcomes back Polina Zvyagina, Director and Executive Lead Counsel for AI & Data Governance at General Motors, for a deep dive into what effective AI governance looks like in practice. From NIST's AI Risk Management Framework to the challenges of AI agents, shadow AI, evaluations, and scalable governance, Polina shares practical insights on building governance that works in the real world. The conversation also examines why governance should function as a "seatbelt, not a brake," helping organizations innovate faster while maintaining trust, transparency, and accountability. They also discuss the importance of human judgment, evaluating AI outputs, fitness-for-purpose testing, and avoiding overreliance on AI systems as organizations scale adoption. For governance leaders, legal professionals, and business leaders alike, this episode offers a important insights for building responsible AI programs that can evolve alongside the technology.
