Event Description
This is the entry point for the "TPRM in the Age of AI" series and the one module every TPRM practitioner should take regardless of seniority. It does not assume any AI background. It starts from first principles: why the attestation model is breaking down, what four real incident case studies say about the gap between declared controls and observable evidence, and what the arrival of AI means for the profession — both the opportunity and the threat.
The module is deliberately uncomfortable in places. It names which parts of the TPRM role are most at risk. It presents the AI-on-AI problem directly: when both the vendor completing the questionnaire and the program reviewing it are using AI, the result is a fast, confident, expensive process that generates zero new information about actual security posture. It also names the structural fact that assessment volume will increase while headcount stays flat — and frames this as something to prepare for, not fear.
Clarence Chio
Co-founder & CEO of Coverbase
UC Berkley Professor
Clarence is the cofounder and CEO of Coverbase, a TPRM copilot that automates 90% of vendor management with AI. Prior to this, he cofounded Unit21, a Google-backed company that raised $92m to help top financial institutions combat fraud and money laundering with AI.
He has degrees in Computer Science and AI from Stanford, published the book "Machine Learning and Security" with O'Reilly Media, and has been teaching AI and security at UC Berkeley since 2019. He has shared his ideas on machine learning and security at DEFCON, BLACK HAT, and other conferences across more than 30 cities.