Artificial intelligence and machine learning have ushered in a new era of opportunity, and unprecedented governance challenges. As organizations race to adopt intelligent systems, the real battleground has shifted from model performance to data readiness, quality, lineage, and ethical controls. This session explores how modern data governance frameworks must evolve to guide AI-driven ecosystems, prevent model drift, reduce digital debt, and deliver trustworthy results at scale.  

Drawing on real-world enterprise experiences, this talk demystifies how AI models interpret and rely on organizational data, why governance failures create exponential downstream risk, and how leaders can build an integrated approach that blends human oversight, automated intelligence, and scalable operational controls. ‍ 

Participants will leave with a practical blueprint for governing machine learning pipelines, strengthening data trust, and preparing their organization for the next generation of AI regulation, innovation, and opportunity 

Speaker: Eric Riz 

President of eMark Consulting 

Eric is a visionary technology entrepreneur with over two decades of industry experience. In 2004, he founded eMark Consulting, a leader in providing Microsoft-based solutions globally. A decade later, he launched VERIFIED™, a data analytics firm acclaimed for its innovative approach to verifying resumes and social profiles. 

As a sought-after public speaker, Eric delivers engaging talks on technology, AI, and entrepreneurship, captivating audiences at major tech events worldwide. His insights have been featured in prominent publications, including The Globe and Mail, Entrepreneur Magazine, Fox Business, and The Huffington Post. 

Eric's expertise in enterprise strategy, data management, and technology governance has led to impactful partnerships with global giants such as Disney and Kellogg’s. He serves on the Microsoft Cloud Advisory Board and has been recognized with six Microsoft MVP awards, underscoring his commitment to innovation and excellence.