The AI Forecast: Data and AI in the Cloud Era

What happens when AI stops advising and starts acting? Agentic AI promises autonomy, speed, and a new level of intelligence in how systems operate. But as these systems begin to pursue goals and make decisions, the risks become harder to predict. In this episode of The AI Forecast, Paul Muller sits down with futurist Nell Watson, AI ethics expert and co-author of “Safer Agentic AI: Principles and Responsible Practices,” to explore what safe, responsible AI looks like in this new era. In this engaging conversation, Nell shares insights from her journey in AI, her work on ethics and safety, and why agentic systems represent a fundamental shift in how we think about risk. From data provenance to governance frameworks, she explains why organizations must move from reactive oversight to proactive design—and why cooperation will be critical to navigating what comes next. Together, Paul and Nell delve into: Why “AI is the butler for the brain” The importance of data provenance in building trustworthy systems How AI ethics and safety must be embedded from the start Why governance needs to anticipate risks, not just respond to them The role of “AI supervising AI” in maintaining control How science fiction can help us prepare for real-world AI challenges If you’re a business or technology leader deploying AI, this episode offers a clear, practical lens on balancing innovation with responsibility—and why safety is now a core requirement for scaling AI systems.   Stay in touch with Nell: Nell Watson on LinkedIn: https://www.linkedin.com/in/nellwatson/ Nell’s website: https://www.nellwatson.com/ Nell Watson’s books on Amazon: https://www.amazon.com/stores/author/B0CWS75KPG To hear more about AI governance, listen to EP 67 | The “Wobbly” Nature of AI: Governing an Unpredictable Technology +++ 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 the Achilles heel of most enterprises. As organizations accelerate AI adoption, boardrooms face urgent questions about cybersecurity, compliance, resilience, and regulatory risk. In this episode of The AI Forecast, Paul Muller meets with Shoshana Rosenberg, author of “Practical AI Governance: Building a Program for Oversight and Strategy,” and creator of the Prism AI Governance Framework, about how leaders can build adaptable AI governance programs that strengthen their resilience to this susceptibility. Drawing parallels with cybersecurity, Shoshana explains why AI is a “wobbly” technology: predictive, non-deterministic, and fundamentally different from traditional software. She explores why governance cannot be owned by a single department and why boards must shift from a compliance mindset to an organizational strategy rooted in adaptability and AI literacy. Their conversation goes in-depth on: Why AI governance is becoming a board-level responsibility How AI differs from traditional deterministic systems Why resilience and adaptability matter more than box-checking compliance The importance of AI literacy across the organization How to balance innovation with risk management Preparing for the evolving AI regulatory environment Board members, CIOs, legal leaders, and AI governance pros: get practical guidance on building AI governance programs that demand trust, defy regulatory scrutiny, and dominate rapid technological change.   Stay in touch with Shoshana: Shoshana on LinkedIn Shoshana’s website  For more on AI governance and cybersecurity, give this episode a listen: Ep 56 | When AI Moves Fast, Security Can't Lag Behind w/ Jessica Hammond +++ 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 this special Women Leaders In Technology episode of The AI Forecast, Wayfound.ai CEO Tatyana Mamut, PhD, makes a bold claim: AI is already acting like a workforce—and organizations are unprepared for what that means.  From econometrics to anthropology to leading roles at Salesforce, AWS, an d Nextdoor, Tatyana shares how her background shaped a fundamentally different approach to leadership. Drawing on her unconventional journey, she explains why agentic AI is forcing leaders to rethink how they manage technology, shifting from systems to a focus on teams, culture, and governance. Together, Tatyana and Paul share their perspectives on: Why agentic AI needs to be managed like human teams The rise of multi-sapien workplaces (humans + AI agents) How culture and leadership frameworks shape AI outcomes Why unstructured data drives the most valuable insights The role of ethics, law, and governance in controlling AI systems Why intellectual curiosity beyond technical skill defines great leaders This conversation goes beyond technology; Tatyana also reflects on leadership and representation in tech, challenging assumptions about opportunity, and exhibiting why diverse ways of thinking are critical in an AI-driven world. Stay in touch with Tatyana: Tatyana Mamut on LinkedIn: https://www.linkedin.com/in/tmamut/  Tatyana’s website: https://www.tmamut.com/  Links & Resources Full Series Playlist: The AI Forecast: Data & AI in the Cloud Era - YouTube Learn more about The AI Forecast: The AI Forecast | Podcast | Cloudera Connect with Cloudera: Website | LinkedIn | YouTube

David Linthicum, seasoned cloud and enterprise architecture analyst and author, shares his pragmatic take on cloud, AI, and resilience. He discusses rising board-level concerns about governance, hidden costs of hybrid and multi-cloud setups, and why workload repatriation is accelerating. He also warns how vibe coding can create inefficient, costly AI applications and urges a common operational control plane for true resiliency.

Charlotte Webb, Marketing and Operations Director at Hive who helps SMEs adopt managed AI services. She discusses cloud myths and hidden costs, the build vs buy tradeoffs, hybrid GPU and Kubernetes infrastructure, data sovereignty and compliance, and how managed services scale e-commerce and reduce AI complexity.

Dipankar Mazumdar, Director of Developer Relations at Cloudera and co-author on lakehouse engineering, explains open lakehouse fundamentals. He covers Apache Iceberg and open table formats, schema evolution, multi-engine access without duplication, small-file pitfalls, cost control for AI compute, and baked-in governance and lineage for production AI.

For decades, success in baseball was built on instinct. Scouts trusted their guts and managers leaned on tradition, meaning experience and unwritten rules shaped decisions that often went unquestioned. Then Billy Beane changed the game. The former Executive VP of Baseball Operations for the Oakland Athletics and pioneer of the Moneyball philosophy joins host Paul Muller on this special episode of The AI Forecast. Together, they explore how evidence-based decision-making disrupted one of the most tradition-bound industries in the world. Billy shares how shifting from intuition to analytics made data the ultimate competitive advantage in baseball. Drawing on hard-won lessons from the front office, he explains how constraints can fuel innovation, why challenging assumptions is essential to performance, and how organizations can use data to redefine the way decisions are made. From talent evaluation to resource allocation, Billy makes the case that optimizing for success means building systems that reward evidence over ego.   Want to hear more about data-driven strategy and transformation? Check out Episode 17: How to Win in the Data Economy with Jan-Willem Middleburg. +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

As telecom operators invest billions in next-generation networks, many are racing to deploy AI to cut costs and unlock new revenue. But beneath the push for automation and smarter infrastructure lies the deeper challenge of rethinking how connectivity itself should be trusted. In this episode of The AI Forecast, Mike O’Sullivan, Head of Member Solutions at TM Forum, joins host Paul Muller to explore how autonomous networks could reshape customer experience and retention. Mike breaks down the financial pressure facing the industry from soaring network build costs, costly legacy systems, and flat revenues, and why cost reduction is only the first step in telecom’s AI journey. Drawing on decades in the industry, Mike paints a clear picture: reactive telecom is out and self-optimizing, AI-powered networks are in. The future of telecom is adaptive and intelligent, and it depends on turning vast amounts of data into immediate, informed action. If you enjoyed this conversation, check out Episode 56: When AI Moves Fast, Security Can’t Lag Behind with Jessica Hammond for more on real-time decisioning and regulated industry AI. Stay in touch with Mike: Mike O’Sullivan on LinkedIn: https://www.linkedin.com/in/mike-o-sullivan-35845b/   +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

As AI and BI projects race to deliver quick wins, many organizations overlook what truly determines long-term success: the people behind the data. In this episode of The AI Forecast, Jen Stirrup, author, speaker, and founder of Data Relish, joins host Paul Muller to dissect the difference between data literacy (reading the numbers) and data fluency (speaking the language of business). Jen challenges the industry’s obsession with AI FOMO, warning that rushing to deploy models on shaky cultural foundations is the fastest way to derail ROI. Drawing on real-world data horror stories, she explains why tools alone cannot fix a broken culture and how mentorship, collaboration, and practical skills can empower teams to work independently and intelligently with data. Listen in to discover: Why poor data culture is the silent killer of AI ROI. How to move your team from passive observation to active questioning. Practical steps to build an environment where it is safe to challenge the data. Did you enjoy this deep dive on data culture? Check out Episode 5: Data Doesn’t Have To Be So Complicated with Jordan Morrow for another perspective on the literacy debate. Stay in touch with Jen: Jen Stirrup on LinkedIn: https://uk.linkedin.com/company/jenstirrup Jen Stirrup’s AI and data books: https://jenstirrup.com/books/  +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

Data complexity is the enemy of innovation. Adam Skotnicky, VP of Engineering at Cloudera and founder of Taikun (acquired by Cloudera), joins host Paul Muller to explain how engineering teams can reclaim simplicity without sacrificing flexibility or control. Together they unpack why most teams are overwhelmed by tooling and operational overhead, how platform engineering can abstract complexity away from users, and what it really means to deliver “cloud-like” agility across hybrid environments. For those dealing with hybrid cloud sprawl, or simply wanting your data platform to do more for you, this episode is a must listen. Stay in touch with Adam:  Adam Skotnicky on LinkedIn: https://www.linkedin.com/in/skotnicky/  +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.