How to adopt an Autonomous approach to AI Governance
2 PM ET
As AI adoption expands across teams, tools, vendors, and workflows, governance programs are under pressure to keep up. Shadow AI, sensitive data exposure, vendor AI risk, and changing regulatory expectations are making manual reviews and policy-only oversight harder to scale.
This session explores how organizations can move towards an autonomous approach to AI governance—a method that helps you prepare for new and emerging risks with rapid AI adoption and ensure readiness without slowing down innovation.
You’ll walk away knowing:
Going AI-First: Tips on Acing SOC 2
AI is rapidly becoming embedded in products, workflows, and decision-making systems. But as organizations move faster with AI, compliance expectations evolve.
SOC 2 in the AI era isn’t harder — it’s different. Controls need to account for dynamic data flows, model usage, third-party AI tools, automation layers, and shifting ownership boundaries. Many teams assume existing compliance programs automatically extend to AI initiatives — but gaps in governance, documentation, and accountability often surface during audit readiness.
This session explores how modern teams can align AI adoption with SOC 2 requirements in a way that strengthens trust while preserving speed. We’ll unpack what changes in an AI-enabled environment, how to think about control maturity, and how to design systems that scale responsibly.
Meet our speaker
Who should attend?
This session is ideal for founders, security leaders, and compliance owners building or scaling AI-enabled systems. If you’re navigating SOC 2 while adopting AI tools, you’ll gain practical clarity on how to stay audit-ready without over-engineering your processes.
Why Organizations Need An Autonomous Approach to AI Governance
