Data Science Leaders

Turning Governance Into the “Yes” Guys

When Cindy Tu [https://www.linkedin.com/in/xin-cindy-tu/] first stepped onto a conference stage, it wasn’t part of a long-term plan. It was a turning point. A single speaking invitation shifted her role from quietly reviewing AI systems to actively shaping how governance is practiced across financial services. With a background spanning IT, data, and audit, Cindy brought a rare systems-level view to the table. Now a rising voice in enterprise AI risk, she’s influencing how institutions think about oversight, how governance frameworks evolve, and why people are at the heart of successful implementation. Her perspective is informed not only by technical expertise, but by lived experience. Cindy brings: * How to frame governance as an enabler and not a gatekeeper * Why third-party risk keeps rising as gen AI adoption accelerates * How to flip governance from the “no” guys to the “yes” guys

Building Trust for Transformation in Enterprise AI

When Shub Agarwal [https://www.linkedin.com/in/shub/] joined an early conversational AI startup, he was building products in uncharted territory with emerging technology few had heard of. By late 2019, Google and Meta were aggressively recruiting him. But a sudden personal loss made him rethink his priorities, leadership, and the impact he wanted to create. From fast-growth startups to a financial regulator, he's codified a nine-step AI product framework, teaches at USC, and developed practical approaches to trust, governance, and AI agents in organizations. His story reflects intentional leadership in a rapidly evolving field. You’ll hear: * How leaders should think about AI agents as part of their teams and workflows * Why stepping back at key moments makes you a better leader * How to evaluate AI systems beyond performance metrics

Engineering the Future of Health with AI and Data

Daniel Kraft [https://www.linkedin.com/in/dkraft/], physician-scientist and founder of NextMed Health [https://nextmed.health/], joins Domino’s Chris McSpiritt to discuss how AI, data convergence, and systems thinking are accelerating healthcare’s shift from reactive treatment to proactive, personalized care. With a background spanning regenerative therapies, digital health, and aerospace medicine, Daniel offers a wide-lens view of the challenges and opportunities shaping the next era of clinical innovation. From the limitations of “sick care” to the promise of personalized poly-pills and AI-powered digital twins, this conversation explores how to unlock proactive, personalized, and accessible healthcare at scale. Join us as we discuss: * How exponential tech is enabling predictive, preventative care and what’s slowing it down * Why “data-to-action” is the next frontier for AI in life sciences * What data scientists and tech teams can do now to drive clinical impact Get more of Daniel’s insights at DanielKraftMD.net [https://danielkraftmd.net].

The Rise of the Self-Driving Organization

As organizations race to become AI-driven, data has emerged not just as a resource, but as a strategic advantage. In this episode, Kjell Carlsson sits down with Doug Laney [https://www.linkedin.com/in/douglaney/], author of Infonomics [https://www.amazon.com/Infonomics-Monetize-Information-Competitive-Advantage/dp/1138090387/ref=sr_1_1?crid=1ZE53ZUJDM57J&keywords=infonomics+douglas+laney&qid=1696449778&sprefix=infonomics+dou%2Caps%2C180&sr=8-1] and Data Juice [https://www.amazon.com/Data-Juice-Organizations-Squeezing-Available/dp/1737169908/ref=sr_1_2?crid=YU0LOBVR6QI2&keywords=data+juice&qid=1696449858&sprefix=data+juice%2Caps%2C162&sr=8-2], to explore how generative AI is accelerating the journey toward data monetization and organizational autonomy. Doug shares why traditional approaches to data management no longer suffice, how digital twins and agentic AI are redefining business models, and why the future may belong to self-driving organizations. Tune in to hear: * How AI is reshaping the economics of data and enabling new business models * Why organizations should embrace agentic AI and digital twins to stay competitive * What leaders must do today to build autonomous, AI-native enterprises

The Cultural Shifts That Power AI Adoption

AI strategy isn't just about technology. It's about transformation. In this episode, CDAO expert, Dr. Shahram Ebadollahi [https://www.linkedin.com/in/shahramebadollahi/], joins to discuss what it takes to lead AI in an enterprise and why that leadership must go far beyond just selecting the right tools or models. Drawing on his experience building AI teams, Shahram explains why the Chief AI Officer role is one of the most complex, and most critical, positions in modern organizations. Here we talk about the cultural, organizational, and strategic shifts needed to embed AI deeply and responsibly, and how to move from experimentation to value delivery at scale. Whether you're leading AI or supporting it, this conversation offers a clear-eyed view of what success really requires. Tune in to hear: * Why the Chief AI Officer must balance tech depth with business vision * How to structure teams and incentives for lasting AI success * How to move from AI experimentation to real business impact