The Data Governance Coach: From Data Error to Insight

The Space-AI-Quantum Nexus Challenging Governance

AI governance is already struggling to keep pace. Add quantum computing and space infrastructure, and the challenge becomes exponentially harder.  In this episode of The AI Forecast, Paul Muller sits down with technology governance specialist and researcher Preetha Bedi to explore the growing convergence between AI, space, and quantum technologies—and why this nexus is creating entirely new categories of systemic risk. From satellite infrastructure and quantum acceleration to agile lawmaking and fractal risk modeling, Preetha makes the case for a fundamentally different approach to technology oversight in the AI era. Paul and Preetha unpack: * Why AI, space, and quantum technologies must be governed as interconnected systems * How traditional governance models are failing to keep pace with technological acceleration * Why agile lawmaking may become essential for emerging technologies * The hidden systemic risks tied to satellite infrastructure and orbital congestion * How quantum computing could dramatically amplify AI development * Why “fractal thinking” helps model repeating patterns in technological risk If you’re thinking about the future of AI governance, this episode offers a thought-provoking perspective on what happens when innovation outpaces institutional control. To hear more about critical infrastructure in space, check out Ep 73 | Out of This World AI: Inside Spaceflight with Jeanette Epps [https://www.youtube.com/watch?v=o8U3MzciWC0&list=PLe-h9HrA9qfAmGHgsmXUZgLL-T4Xjhlq8]  Stay in touch with Preetha: Preetha Bedi on LinkedIn: https://www.linkedin.com/in/preethabedi/ +++ Like and subscribe to The AI Forecast, sponsored by Cloudera, to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.

Why Enterprise AI Still Breaks at Scale with Ravit Jain

As organizations rush to scale AI, many are learning that better models can’t compensate for weak data foundations. AI hype is everywhere, but operational readiness still isn’t. In this episode of The AI Forecast, Paul Muller sits down with Ravit Jain, founder of The Ravit Show and one of the leading voices in the global data and AI community, to explore the trends shaping the future of enterprise AI. Drawing on conversations with hundreds of AI and technology leaders, Ravit shares why the industry is shifting away from experimentation and toward measurable business outcomes. From agentic systems and contextual AI to governance and responsible adoption, he explains why organizations must get the fundamentals right before AI can scale effectively. Together, Paul and Ravit delve into: * Why data quality remains the foundation of successful AI * How AI is moving from assistant to operator * The rise of agentic AI and contextual systems * How governance and responsible AI shape long-term adoption * Why operational readiness matters as much as the technology itself If you’re building or scaling enterprise AI, this episode offers a practical perspective on separating hype from impact, and what leaders should prioritize as AI moves into its next phase. To hear more about the future of enterprise AI, check out Ep 69 | Industrial Enterprise AI: Growing Value and Organizational Risk Management [https://www.youtube.com/watch?v=zrrK114Eu2o&list=PLe-h9HrA9qfAmGHgsmXUZgLL-T4Xjhlq8&index=5].   Stay in touch with Ravit: Ravit Jain on LinkedIn: https://www.linkedin.com/in/ravitjain/ [https://www.linkedin.com/in/ravitjain/]  Ravit Jain’s website: https://www.theravitshow.com/ [https://www.theravitshow.com/]  The Ravit Show on YouTube: https://www.youtube.com/channel/UC4yopSSlBfw2WAykLPTYH-w [https://www.youtube.com/channel/UC4yopSSlBfw2WAykLPTYH-w]  +++ Like and subscribe to The AI Forecast, sponsored by Cloudera, to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast [https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.youtube.com%2F%40ClouderaInc%2Fpodcasts&data=05%7C02%7C%7Cd0f591f5f3614efdbbdc08dd56b23491%7Cbf0b48c768944eb6bf538621676ccee4%7C0%7C0%7C638762045578093614%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=Srpaog%2FcvZzEfMiUXfJXslY9nSM%2BK622y9j2zOlhxZk%3D&reserved=0].

Fan Intelligence: Preparing for the World Cup Surge

With the World Cup on the horizon, global attention is about to shift back to football. For clubs, that spotlight represents a rare opportunity to activate millions of fans. The question is whether they’re ready. As AI reshapes how organizations understand and engage their customers, sports clubs are beginning to rethink what a “fan” really is. In markets like Brazil, where membership programs are a core part of club revenue, teams hold vast amounts of fan data, but it is often fragmented. Ticketing systems, membership programs, e-commerce, and social channels often operate in silos, making it nearly impossible to build a unified view of the fan. In this episode of The AI Forecast, Paul Muller sits down with Caio Nogueira, co-founder of Lupa Data, to explore how AI and data are transforming fan engagement—and why most clubs are still leaving value on the table. Caio and Paul explore the implications of: * Why fan data is becoming a measurable business asset * The shift from static databases to dynamic, behavior-driven segmentation * Using AI to predict churn, personalize experiences, and drive loyalty * How leading organizations are moving toward behavior-based segmentation, using data to understand how fans engage (and when they disengage) For any organization managing subscribers or members, the tools to understand your audience already exist. The challenge is bringing the data together in a way that makes it usable. Because when the next global moment arrives, the advantage goes to the teams that already know their fans. To explore another data-driven transformation in sports, check out Ep 62 | How Moneyball's Billy Beane Changed Baseball Forever with Data Analytics [https://www.youtube.com/watch?v=RZo90YbHtR8&list=PLe-h9HrA9qfAmGHgsmXUZgLL-T4Xjhlq8&index=11]    Stay in touch with Caio: Caio Nogueira on LinkedIn: https://www.linkedin.com/in/caio-nogueira-gon%C3%A7alves-52529837/ +++ Like and subscribe to The AI Forecast, sponsored by Cloudera, to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast [https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.youtube.com%2F%40ClouderaInc%2Fpodcasts&data=05%7C02%7C%7Cd0f591f5f3614efdbbdc08dd56b23491%7Cbf0b48c768944eb6bf538621676ccee4%7C0%7C0%7C638762045578093614%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=Srpaog%2FcvZzEfMiUXfJXslY9nSM%2BK622y9j2zOlhxZk%3D&reserved=0].

Out of This World AI: Inside Spaceflight with Jeanette Epps

Human spaceflight is one of the few domains in which data and human judgment must work together flawlessly under extreme pressure. That makes it a powerful lens for understanding what it takes to build resilient, intelligent systems here on Earth. In this Women Leaders in Technology spotlight episode of The AI Forecast, Paul Muller sits down with former NASA astronaut Dr. Jeanette Epps to explore what complex, high-stakes environments can teach us about AI. Drawing on her 235-day mission aboard the International Space Station, Jeanette shares firsthand insights into how tightly integrated systems must function when precision is critical, and uncertainty is unavoidable. From working with autonomous robotic systems like Astrobee to managing unexpected mission anomalies, her experience proves that automation works best when paired with human judgment, not separated from it. On today’s mission, Jeanette and Paul chart a course through: * What human spaceflight reveals about managing complex systems * Why precision and trust are non-negotiable in mission-critical environments * The role of human-in-the-loop decision-making in AI systems * Lessons in leadership, resilience, and decision-making under pressure * Why baseline testing and known data are essential for trusting AI outputs * How to design systems that balance automation with human oversight For leaders building AI-driven systems, this episode offers a rare perspective from one of the most demanding operational environments imaginable. When the stakes are high enough, there’s no room for guesswork—only systems you can trust. To listen to another episode from the WLIT series, check out Ep 66 | Women Leaders in Technology: AI Agents Are Your New Team– Now What? [https://www.youtube.com/watch?v=vaOkegzc6XI&list=PLe-h9HrA9qfAmGHgsmXUZgLL-T4Xjhlq8&index=7]    Stay in touch with Jeanette: Dr. Jeanette Epps on LinkedIn: https://www.linkedin.com/in/jeanette-epps-phd-812aba50/ Dr. Jeanette Epps on Instagram: https://www.instagram.com/jeanette.epps/ +++ Like and subscribe to The AI Forecast, sponsored by Cloudera, to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast [https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.youtube.com%2F%40ClouderaInc%2Fpodcasts&data=05%7C02%7C%7Cd0f591f5f3614efdbbdc08dd56b23491%7Cbf0b48c768944eb6bf538621676ccee4%7C0%7C0%7C638762045578093614%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=Srpaog%2FcvZzEfMiUXfJXslY9nSM%2BK622y9j2zOlhxZk%3D&reserved=0].

The Data Governance Coach: From Data Error to Insight

In the world of enterprise AI, the pressure on data has changed. What used to be “good enough” now gets amplified by faster decisions, and therefore, faster mistakes. Governance is fundamental in ensuring data trust and integrity. In this episode of The AI Forecast, Paul Muller sits down with The Data Governance Coach, Nicola Askham, to share her pragmatic perspective and assert that governance only delivers value when it’s simple enough for people to use and embedded into day-to-day work. Here’s what business leaders need to know: * Why data governance has shifted from compliance to value creation * How AI is raising the stakes for data quality and trust * Practical ways to start and scale governance without overengineering it * Why data governance is more about people than technology * Common anti-patterns, from “IT-owned governance” to overly complex frameworks * The role of data literacy and communication in driving adoption * How to design fit-for-purpose frameworks that evolve with the organization Nicola’s advice is refreshingly direct: start small, keep it simple, and focus on outcomes. In a world shaped by AI, governance evolves alongside the business, sharpening decision-making and protecting against costly mistakes.  For more on data governance, listen to Ep 68 | Agentic AI Is Forcing a Governance Reset [https://www.youtube.com/watch?v=C_SN70c6-M4&list=PLe-h9HrA9qfAmGHgsmXUZgLL-T4Xjhlq8&index=3].   Stay in touch with Nicola: Nicola Askham on LinkedIn: https://www.linkedin.com/in/nicolaaskham/ Nicola’s website: https://www.nicolaaskham.com/ Nicola’s book on Amazon: https://www.amazon.com/Effective-Data-Governance-Framework-Organization-ebook/dp/B0FY7KWSM8?ref_=ast_author_dp&th=1&psc=1 +++ Like and subscribe to The AI Forecast, sponsored by Cloudera, to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast [https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.youtube.com%2F%40ClouderaInc%2Fpodcasts&data=05%7C02%7C%7Cd0f591f5f3614efdbbdc08dd56b23491%7Cbf0b48c768944eb6bf538621676ccee4%7C0%7C0%7C638762045578093614%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=Srpaog%2FcvZzEfMiUXfJXslY9nSM%2BK622y9j2zOlhxZk%3D&reserved=0].