The AI Forecast: Data and AI in the Cloud Era

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 
Stay in touch with Marlon:
Marlon Davis on LinkedIn: https://www.linkedin.com/in/marlondavis/
Froogel Product Manager Newsletter: https://www.linkedin.com/in/marlondavis/recent-activity/newsletter/ 
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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 
Stay in touch with Michael:
Michael Gray on LinkedIn: https://www.linkedin.com/in/michael-gray-4861663/
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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 
Stay in touch with John:
John Capobianco on LinkedIn: 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
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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.

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 
Stay in touch with Preetha: Preetha Bedi on LinkedIn: https://www.linkedin.com/in/preethabedi/
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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.

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.
 
Stay in touch with Ravit: Ravit Jain on LinkedIn: https://www.linkedin.com/in/ravitjain/ 
Ravit Jain’s website: https://www.theravitshow.com/ 
The Ravit Show on YouTube: https://www.youtube.com/channel/UC4yopSSlBfw2WAykLPTYH-w 
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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.

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 
 
Stay in touch with Caio:
Caio Nogueira on LinkedIn: https://www.linkedin.com/in/caio-nogueira-gon%C3%A7alves-52529837/
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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.

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? 
 
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/
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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.

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.
 
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
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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.

AI ambition is everywhere. The models are ready, the investment is flowing, yet the outcomes aren’t keeping up. 
Cloudera’s Data Readiness Index 2026  survey identifies a widening gap between what enterprises want from AI and what they can actually deliver. In this episode of The AI Forecast, Paul Muller sits down with Cloudera CTO Sergio Gago to bring a practitioner’s lens to the problem, drawing on experience across the full spectrum from startups to global enterprises. 
Together, they unpack the survey to find out what’s really holding enterprise AI back:
Why enterprise AI adoption stalls between pilot and production
How fragmented data ecosystems limit AI effectiveness
How data accessibility limits AI impact
The growing importance of data quality and trust
The critical role of governance in enabling AI at scale
The shift from “hybrid by accident” to hybrid by design in modern architectures
How data readiness determines whether AI delivers real ROI
As coding becomes faster and cheaper through AI, the bottleneck is moving upstream to trustworthy, well-governed data. For technology leaders, AI success depends on building the right data foundation.
 
Stay in touch with Sergio: Sergio Gago on LinkedIn: https://www.linkedin.com/in/sergiogh 
Sergio’s Quantum Pirates Newsletter: https://quantumpirates.substack.com/ 
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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.

As AI adoption accelerates, so do the risks that come with it. So what happens when AI puts cyberattack capabilities into everyone’s hands?
In this episode of The AI Forecast, Paul Muller is joined by Theresa Payton to break down the new reality of AI-powered threats. Drawing on decades of experience as the first female White House CIO, CEO of Fortalice Solutions, and the author of four books on privacy and big data, Theresa explains why AI has fundamentally changed the rules of cybersecurity and why most organizations are still playing catch-up.
From deepfakes and automated attacks to data poisoning and quantum disruption, Theresa makes the case that cybersecurity must evolve from a siloed function into an enterprise-wide mindset.
Paul and Theresa offer insights into:
The rise of AI-driven cybercrime at speed and scale
Why data lifecycle and classification matter more than ever
The risks and rewards of autonomous and self-healing systems
The hidden dangers of vibe coding and unsecured AI adoption
Why trust is a measurable business asset
For leaders navigating AI transformation, this episode is a wake-up call to focus on mitigating today’s risks before they become tomorrow’s breaches.
Want to know more about vibe-coding?  Check out Ep 65 | The Vibecoding Liability: How Unchecked AI Can Kill Cloud ROI. 
 
Stay in touch with Theresa:Theresa Payton on LinkedIn: https://www.linkedin.com/in/theresapayton/
Theresa’s website: https://www.theresapayton.com/
Theresa’s books on Amazon: https://www.amazon.com/stores/Theresa-Payton/author/B007ECYE4K?ref=ap_rdr&shoppingPortalEnabled=true
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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.