Out of This World AI: Inside Spaceflight with Jeanette Epps

Why Some AI Products Strike a Chord (and Others Don't)

You recognize the tune, but something feels off. That's how Marlon Davis describes many of today's AI initiatives: AI karaoke. Organizations are rushing to add AI to products, but too often they're layering technology onto solutions without fully understanding the customer problems they're trying to solve. In this episode of The AI Forecast, Paul Muller sits down with fractional Chief Product Officer at Devlnio, Marlon Davis, to explore how organizations can move beyond superficial AI efforts and build products that deliver meaningful customer value.  Paul and Marlon take a closer look at: * How to identify opportunities where AI genuinely creates value * Why product teams should focus on customer problems before AI solutions * The importance of anthropology and observing customer behavior * How AI can improve product operations and decision-making * Why understanding customer workflows matters more than adding AI features * How product managers can navigate the rise of AI-assisted development If you're deciding where AI belongs in your product portfolio, this episode provides a grounded approach to identifying opportunities that matter to customers.  To hear more about turning AI investments into business value, check out Ep 78 | Mastering Enterprise AI: Why Some Projects Succeed While Others Fail [https://www.youtube.com/watch?v=_0dLMkjbxVw&list=PLe-h9HrA9qfAmGHgsmXUZgLL-T4Xjhlq8]  Stay in touch with Marlon: Marlon Davis on LinkedIn: https://www.linkedin.com/in/marlondavis/ [https://www.linkedin.com/in/marlondavis/] Froogel Product Manager Newsletter: https://www.linkedin.com/in/marlondavis/recent-activity/newsletter/  [https://www.linkedin.com/in/marlondavis/recent-activity/newsletter/] +++ 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.

Mastering Enterprise AI: Why Some Projects Succeed While Others Fail

AI may be the most capable intern your organization has ever hired. However, interns still need guidance and clear direction. Enterprise AI is proving no different. In this episode of The AI Forecast, Paul Muller sits down with Michael Gray, CTO of Thrive, to explore the patterns and anti-patterns emerging from real-world enterprise AI deployments.  Drawing on his experience helping organizations implement AI at scale, Michael offers a practical framework for evaluating AI maturity, helping leaders understand where adoption breaks down and what it takes to build momentum across the organization.  Paul and Michael take a closer look at: * Why AI adoption often stalls despite significant technology investments * The role of organizational change management in successful AI programs * Common AI adoption patterns and anti-patterns across enterprises * How champions inside the organization can accelerate AI success * How governance and security evolve as AI scales * The importance of focusing on business outcomes rather than technology alone The path from AI investment to business value is often more complex than expected. This episode offers advice on turning AI investments into measurable outcomes while building the organizational foundations for successful scaling.  To hear more about the organizational challenges facing AI adoption, 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=9]  Stay in touch with Michael: Michael Gray on LinkedIn: https://www.linkedin.com/in/michael-gray-4861663/ +++ 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.

The Rise of VibeOps: How AI Is Transforming Network Automation

For decades, network teams have been forced to choose between speed and stability. AI may finally be changing that equation. In this episode of The AI Forecast, Paul Muller sits down with John Capobianco, Head of AI and Developer Relations at Itential and author of “Automate Your Network,” to explore how AI is reshaping the future of network operations. Drawing on decades of experience in network engineering, John explains why network automation has struggled to gain traction and how AI, agents, and Model Context Protocol (MCP) could finally break the bottleneck.  Paul and John take a closer look at: * Why network automation adoption has lagged behind other areas of IT * How AI can augment network engineers instead of replacing them * The role of MCP and AI agents in automating complex workflows * Why “AI can write and validate scripts as a pair programmer” * How digital twins can reduce risk and improve network resilience * The emergence of VibeOps and AI-driven operations For technology leaders navigating AI adoption, this episode explores how AI-powered automation can help network teams move faster without sacrificing reliability. To hear more about AI-powered operations and vibecoding, check out Ep 65 | The Vibecoding Liability: How Unchecked AI Can Kill Cloud ROI [https://www.youtube.com/watch?v=dnsXTVOj5qk]  Stay in touch with John: John Capobianco on LinkedIn: https://www.linkedin.com/in/john-capobianco-644a1515/ [https://www.linkedin.com/in/john-capobianco-644a1515/] John’s website: https://www.automateyournetwork.ca/home/ “Automate Your Network” on Amazon: https://www.amazon.com/Automate-Your-Network-Introducing-Enterprise/dp/1799237885 +++ 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.

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].