As AI adoption accelerates, so do the risks. In this episode of The AI Forecast, Jessica Hammond—Senior Director Product Management of GenAI at Protegrity—joins host Paul Muller to unpack how organizations can move fast with AI without compromising security, privacy, or compliance.
Drawing on her background in product, engineering, security, and compliance, Jessica explains why sensitive data exposure is one of the most underestimated risks in AI systems—from user-generated inputs leaking PII to agents inheriting permissions they shouldn’t have. She walks through how field-level data protection, policy-based controls, and governance embedded directly into the AI pipeline can protect data transparently, without slowing developers or re-architecting applications.
The conversation also explores why governance can’t be bolted on at the end, how data protection impacts AI evaluations and non-deterministic outputs, and what it really takes to secure AI across hybrid and multi-cloud environments.
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