Trustworthy AI : De-risk business adoption of AI

Description: Creating AI Trust is a very complex and hard problem. It is not clear what it is and how it can be operationalized. We will demystify what is Trustworthy AI, efficient adoption and leveraging it for reducing risks in AI programs.
McKinsey reports indicates companies seeing the biggest bottom-line returns from AI—those that attribute at least 20 percent of EBIT or profitability to their use of AI—are more likely than others to follow Trustworthy AI best practices, including explainability. Further, organizations that establish digital trust among consumers through responsible practices such as making AI explainable are more likely to see their annual revenue and profitability grow at rates of 10 percent or more.

Host

Pamela Gupta

"I'm Pamela Gupta—2025 Wasserman Award Honoree for AI Governance, ranked globally in the top 3 for Risk Management and top 7 for Cybersecurity.

I help organizations embrace AI confidently by building governance frameworks that enable innovation instead of blocking it.

I've operationalized AI governance across 120 countries, advised the U.S. Department of Defense, and enabled critical infrastructure companies to launch stalled AI initiatives in 60 days.

I created the AI TIPS framework four years before NIST published their AI Risk Management Framework. I've built AI Centers of Excellence, designed automated governance platforms, and created security guardrails that developers actually want to use.

My expertise spans ISO 42001, NIST AI RMF, EU AI Act, and Zero Trust architecture—but more importantly, I know how to make them work in the real world.

Because AI governance isn't about saying no—it's about enabling yes, safely."