What if you could measure the trustworthiness of an AI system the same way you audit financial controls? As GenAI and autonomous agents move from pilots into production, "responsible AI" too often stops at principles — leaving teams without a concrete way to prove a system is safe before it ships. This talk introduces a measurable approach to AI trust and safety, drawing on an 8-pillar, 93-test evaluation framework aligned to NIST AI RMF, the EU AI Act, OWASP, and ISO 42001, plus an emerging "SOC 2 for agents" certification model. Attendees will leave with a practical scorecard for evaluating GenAI and agentic systems, the metrics that matter most for enterprise deployment, and a clear view of where trust becomes a competitive advantage rather than a checkbox. If you're responsible for getting AI into production safely — and proving it — this session gives you the language and the tools to do it.
