Ioana Tanase, AI and Accessibility @ Microsoft, dives deep into what makes AI truly trustworthy—and why it’s more than just technology. From Responsible AI principles to AI governance, this video explains how organizations can build systems that people trust and use confidently.

There is no AI without data, and that to be trustworthy, AI requires trustworthy data. An obvious manifestation the Data Divide is the separation between the data "have" and "have not" organizations. Put another way, organizations possessing relevant, clean data sets stored in modern, AI-addressable data technologies enjoy a massive advantage in what AI can do for them, and in how quickly they can bring it to bear in service of the challenges they face. This is fast becoming a critical asset for organizations. The next couple of years will see a stark separation in fortunes for these have and have not organizations.

In this conversation, Andrew Welch and Steve discuss the evolving landscape of AI, particularly focusing on the importance of trustworthy AI, governance, and the role of data. They explore the challenges faced by organizations in adopting AI technologies, the concept of vibe coding, and the differing perspectives on AI, including optimism and skepticism. The discussion highlights the need for a balanced approach to AI implementation, emphasizing the importance of technical expertise and the potential pitfalls of relying solely on AI without proper understanding and governance.

Join us for a focused, high-utility conversation where Financial Services CIO and AI strategy leaders from Xponance, Damco, and Cloud Lighthouse unpack how to move beyond experimentation and design AI programs that are governed, auditable, and business-aligned from Day 1.

New AI regulations and board-level scrutiny are arriving faster than most enterprises can adapt. In this executive briefing you’ll get a crash course on how to build, govern, and scale AI responsibly; without slowing innovation.