The AI Forecast: Data and AI in the Cloud Era

Most enterprise AI use cases still aren't delivering measurable value. So what separates the projects that work from the ones that quietly disappear? For Mark Ritcey, the answer comes down to disciplined execution. AI programs need a clear business problem and an organization prepared for how the technology changes the way work gets done. In this episode of The AI Forecast, Paul Muller sits down with Mark Ritcey, Vice President of AI and Automation Delivery at Latentbridge and lecturer on AI and machine learning, to examine the decisions that shape enterprise AI success. Mark has spent more than 25 years working across technology and automation, including leading enterprise transformation initiatives in highly regulated industries. He shares what he’s seeing inside AI programs today, where teams commonly go wrong, and why structured experimentation matters as organizations figure out where AI can create real value. What separates AI success from failure, according to Mark and Paul: Why AI projects need a clearly defined business problem The risks of experimenting with AI for its own sake How unrealistic expectations derail enterprise deployments The role of governance as AI moves into production How organizational change affects AI adoption What CEOs and boards should consider before scaling AI His advice for leaders is refreshingly straightforward: AI transformation requires diligent, structured work. There are no shortcuts around understanding the business and building the controls required to put AI into production responsibly. Want to hear another perspective on enterprise AI adoption? Check out Ep 78 | Mastering Enterprise AI: Why Some Projects Succeed While Others Fail.   Stay in touch with Mark: Mark on LinkedIn: https://www.linkedin.com/in/markritcey/  +++ 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 a humanitarian crisis, waiting for perfect information isn't an option. Every decision must be made with incomplete data and limited resources in a situation that can change by the hour. For organizations like Mercy Corps, AI is helping teams make sense of that uncertainty. By bringing together information from conflict reports, local media, humanitarian data, and environmental sources, AI can surface the context decision-makers need while leaving human judgment firmly in their hands. In this episode of The AI Forecast, Paul Muller is joined by Josh DeWald, Vice President of Technical Support, Evidence and Program Quality at Mercy Corps, and Rob Dickens, AI Technical Lead at Cloudera. Together, they explore how VERA, an agentic AI platform co-developed by Cloudera and Mercy Corps, is helping humanitarian teams gather information faster and make better-informed decisions.  Inside their discussion: How AI supports humanitarian decision-making during fast-moving crises Why data collection is so difficult in conflict-affected regions How agentic AI combines structured and unstructured information The importance of human oversight in AI-assisted decisions Protecting data privacy and reducing bias in humanitarian AI Lessons enterprise organizations can learn from operating in information-poor environments How AI is improving organizational learning across humanitarian programs The conversation explores what responsible AI looks like when decisions carry humanitarian consequences. Whether you're leading enterprise AI initiatives or working in mission-driven organizations, this episode offers valuable insights into building AI systems that help people make better decisions when the stakes are highest. Stay in touch with Josh and Rob: Josh DeWald on LinkedIn: https://www.linkedin.com/in/josh-dewald-10a6178b/?skipRedirect=true Rob Dickens on LinkedIn: https://www.linkedin.com/in/robert-dickens-73a91340/?skipRedirect=true&originalSubdomain=uk +++ 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.

Your dashboard can tell you sales are down, but it can't tell you why or what to do next. Dashboards have become the default way to monitor a business. Bhaskar Sunkara argues they're only the starting point. The next step is AI that understands business context and helps leaders move from insight to action.  In this episode of The AI Forecast, Paul Muller sits down with the founder and CEO of Bicycle AI to explore how agentic AI is reshaping enterprise analytics. After helping pioneer application monitoring, Bhaskar now focuses on a different question: how AI can help businesses understand why something changed and what action to take next.  Bhaskar and Paul break down: Why traditional dashboards fall short for business decision-making How agentic AI moves from reporting problems to recommending actions The role of business ontology in connecting data, context, and outcomes Why data quality and traceability remain essential for trustworthy AI How AI can automate root cause analysis across technical and business systems Why human judgment remains central to enterprise decision-making What it takes to build proactive, AI-driven business operations Bhaskar sees AI as a force multiplier for decision-makers, assembling the evidence so leaders can focus on judgment and accountability. The result is faster, more informed decisions backed by business context. Want to learn more about enterprise AI decision-making? Check out Ep 80 | Decision Logic: The Difference Between an Answer and a Decision    Stay in touch with Bhaskar: Bhaskar Sunkara on LinkedIn: https://www.linkedin.com/in/bhaskarsunkara/ +++ 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.

Behavior change is the biggest hurdle in AI adoption. AI only creates value when people make it part of their everyday work. In this episode of The AI Forecast, Paul Muller sits down with Varun Puri, CEO and co-founder of Yoodli, to discuss why successful AI adoption starts with changing how people work. Drawing on his experience at Google, Google X, and as the founder of an AI startup, Varun shares practical lessons on embedding AI into everyday workflows and building habits that stick. From AI-generated leadership briefings to a daily gratitude agent, Varun explains how small behavioral shifts can unlock outsized results, and why the most valuable AI tools are the ones people actually use. Varun and Paul’s conversation explores: Practical ways startups are using AI to improve daily operations How AI gives leaders real-time visibility across the business Why incentives often undermine successful AI initiatives Why emotional intelligence may become more valuable in the AI era Personal AI workflows that help leaders stay focused and effective Throughout the discussion, Varun explains how AI becomes most valuable when it helps people do their best work, rather than simply automating tasks.  Whether you're rolling out AI across an enterprise or scaling a startup, this episode offers practical ideas for integrating AI into everyday work.  Want to hear more about leading successful AI adoption? Check out Ep 78 | Mastering Enterprise AI: Why Some Projects Succeed While Others Fail  Stay in touch with Varun: Varun Puri on LinkedIn: https://www.linkedin.com/in/varun-puri001 +++ 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 is already inside your organization. The question is whether you know where. As Lisa Pent says, “You can’t govern what you can’t see.”  In this episode of The AI Forecast, Paul Muller sits down with Lisa Pent, CEO and Founder of PentEdge, to discuss why AI visibility is becoming a board-level issue and what organizations can do to govern AI with confidence. Lisa makes the case that visibility is the foundation of effective AI governance.  Throughout her career in investment banking and fintech, Lisa explains why AI governance must move beyond policies and annual audits. She explains how organizations can gain visibility into AI use and build stronger governance around it.  Their conversation explores: Why AI governance must become continuous How data lineage creates a stronger audit trail The risks created by shadow AI How to assess AI risk across critical business systems What boards should be asking about AI oversight Practical ways to monitor AI across the enterprise If AI is becoming part of your organization, this conversation provides a practical framework for effective oversight. To hear more about governing data in the age of AI, check out Ep 72 | The Data Governance Coach: From Data Error to Insight.   Stay in touch with Lisa: Lisa on LinkedIn: https://www.linkedin.com/in/lisapent/ +++ 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.

Ask an AI system a question, and you'll get an answer. Decision logic determines whether you should trust it.  In this episode of The AI Forecast, Paul Muller sits down with Darlene Newman, Innovation Lead at Duczer East, to explore the hidden layer that helps AI move from pattern matching to practical decision-making.  From semantic layers and ontologies to knowledge graphs and governance frameworks, Darlene unpacks the often-overlooked structures that sit between AI outputs and real-world decisions. She also shares practical guidance on integrating decision-making logic into AI initiatives without adding complexity. Paul and Darlene take a closer look at: Why decision logic is the “why” behind AI decisions How guardrails help prevent hallucinations and unreliable outputs Why knowledge design is becoming a critical AI capability How organizations can build scalable and auditable AI systems Practical approaches for integrating decision logic into AI initiatives Beyond models and prompts, this conversation is about giving AI the context it needs to make better decisions. For enterprise leaders, it offers a practical look at the structures and knowledge foundations that can help AI deliver consistent business outcomes. To hear more about turning organizational knowledge into AI capabilities, check out Ep 69 | Industrial Enterprise AI: Growing Value and Organizational Risk Management  Stay in touch with Darlene: Darlene Newman on LinkedIn: https://www.linkedin.com/in/darlenenewman/ Where Innovation Takes Root newsletter: https://www.linkedin.com/newsletters/innovation-through-the-hype-7272737391067459584/ +++ 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.

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/  +++ 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/ +++ 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  +++ 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/ +++ 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/ +++ 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 +++ 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/  +++ 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 +++ 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.

Enterprise AI is running into a familiar problem in the energy and manufacturing industries: the technology is moving faster than the organizations around it. In this episode of The AI Forecast, Paul Muller sits down with Patrick Bangert, VP and Chief of AI at Occidental Petroleum, and author of “Leading Enterprise AI Programs: Optimize AI Teams for Value Creation,” to unpack the complexities of rolling out AI at enterprise scale in highly regulated industries with serious physical risks and 24/7 operations. Together, Paul and Patrick take a closer look at: How machine learning solves complex physical problems with predictive maintenance Organizational change management when responses are emotional Why reinventing organizational processes is key to AI success The rise of shadow AI and startups as drivers of innovation Why responsible AI and governance are essential for scaling safely How to balance experimentation with long-term AI effectiveness For leaders navigating enterprise AI in industrial settings, this episode offers a grounded, practical perspective on what separates hype from impact, and how to build an AI strategy that actually delivers. Want to know more about the obstacles facing enterprise AI? Check out Ep 48 | Why Most Enterprise AI Projects Fail and How to Fix Them with Tom Harshbarger   Stay in touch with Patrick: Patrick Bangert on LinkedIn: https://www.linkedin.com/in/patrick-bangert/  +++ 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.

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

Cloud computing promised efficiency, scalability, and reliability. But as AI workloads grow more complex, many enterprises are learning the hard way that these promises don’t come automatically.   In this episode of The AI Forecast, Paul Muller sits down with Linthicum Research founder David Linthicum to talk through the real state of hybrid cloud strategy and enterprise architecture in the age of cloud computing and AI. Together, Paul and David delve into:  Why cloud governance and resilience are now board-level concerns The hidden costs of hybrid cloud and multi-cloud environments Why workload repatriation is accelerating How vibe coding can generate inefficient, high-cost AI applications The difference between reliability and true operational resilience Why enterprises need a common operational control plane If you’re a technology leader scaling AI systems, this episode offers practical guidance on building governed, cost-efficient cloud architectures that won’t fail as complexity rises.  To go deeper on cloud resilience, hybrid cloud strategy, and AI workloads, listen to Ep 59 | The Secret to Creating the Cloud-Like Experience Anywhere with Adam Skotnicky.   Stay in touch with David: David Linthicum on LinkedIn: https://davidlinthicum.com/about-david-linthicum  David’s website: https://davidlinthicum.com/about-david-linthicum    +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.   Links & Resources Full Series Playlist: https://www.youtube.com/playlist?list=PLe-h9HrA9qfAmGHgsmXUZgLL-T4Xjhlq8  Learn more about The AI Forecast: https://www.cloudera.com/resources/podcast/the-ai-forecast.html    Connect with Cloudera: Website | LinkedIn | YouTube

AI adoption is accelerating across small and medium-sized enterprises (SMEs), but many businesses lack the in-house expertise to build and manage AI infrastructure effectively.  In this episode of The AI Forecast, Paul Muller speaks with Hyve’s Marketing and Operations Director, Charlotte Webb, about how managed service providers (MSPs) are reshaping AI adoption for SMEs. They explore the build vs. buy debate in AI solutions and why cloud computing alone doesn’t guarantee lower costs, better performance, or compliance.  Charlotte explains how Hive takes a consultative approach to AI managed services—helping businesses align AI initiatives with long-term business strategy, digital transformation goals, and operational efficiency.  Charlotte and Paul dive headfirst into:   The risks of unmanaged AI workloads in the cloud  The role of managed services in reducing complexity and cost  Data sovereignty and regulatory compliance in AI deployments  Misconceptions about cloud computing and AI performance  Hybrid cloud and GPU infrastructure for scalable AI workloads  Real-world AI success stories, including e-commerce growth and operational gains  For those navigating AI adoption, evaluating cloud strategy, or exploring managed AI services, this episode provides actionable insights into building sustainable AI capabilities without overextending internal resources.    Stay in touch with Charlotte:  Charlotte on LinkedIn  Want to hear more about the build vs buy debate and lessons from the cloud computing era? Check out Ep 28 | Engineering for GenAI: Lessons from Past Hype Cycles with Ryan Ries of Mission Cloud    +++  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.    Links & Resources Full Series Playlist: https://www.youtube.com/playlist?list=PLe-h9HrA9qfAmGHgsmXUZgLL-T4Xjhlq8  Learn more about The AI Forecast: https://www.cloudera.com/resources/podcast/the-ai-forecast.html    Connect with Cloudera: Website | LinkedIn | YouTube

Open lakehouse architecture is becoming the foundation for production AI and enterprise AI at scale.  In this episode of The AI Forecast, Dipankar Mazumdar, Director of Developer Relations at Cloudera and co-author of the book “Engineering Lakehouse with Open Table Formats,” joins Paul Muller to explain why open lakehouse architecture is critical for moving from AI pilot to production AI.  They break down:  How Apache Iceberg and open table formats decouple storage from compute How schema evolution enables change without costly data rewrites How multiple engines can securely access the same data without duplication How to prevent small-file performance bottlenecks How to control AI compute costs at scale How to embed governance, metadata, and data lineage into AI workloads  Production-ready AI requires scalable data architecture and governance built in from day one. AI and GenAI pilots may be everywhere, but your architecture is what truly decides what survives.   Stay in touch with Dipankar:   Dipankar Mazumdar on LinkedIn: https://www.linkedin.com/in/dipankar-mazumdar/  Dipankar’s website: https://dipankarmazumdar.github.io/  Dipankar’s book on Amazon: https://www.amazon.com/Engineering-Lakehouses-Open-Table-Formats-ebook/dp/B0DKJD39X8    +++  Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise 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.

AI is reshaping how sales teams find prospects, build relationships, and close deals. Frank O’Dowd, Cloudera’s Chief Revenue Officer, joins to discuss Cloudera’s approach to AI in the sales function.  Frank details his philosophy, which is that rather than replacing the human touch, AI is helping sales professionals work smarter, offering insights, personalization, and efficiency at scale. It’s a complementary tool that can help sales teams make themselves relevant to their target audience.  As Frank says in the episode, “The person with the most information always wins.”  Stay in touch with Frank:  Frank O’Dowd on LinkedIn: linkedin.com/in/frank-o-dowd-262508  +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

One common cause of concern around AI is how its computing may negatively impact the environment. In this episode of The AI Forecast, Julie Kae, VP of Sustainability and Social Impact at Qlik and Executive Director of Qlik.org, joins host Paul Muller to reframe the conversation: when designed intentionally, AI isn’t a threat to ESG: it can be one of its most powerful enablers. Drawing on more than 15 years leading data-for-good initiatives, Julie explains how AI and analytics can help organizations reduce waste, lower emissions, and create measurable social impact, without sacrificing profitability. She shares real-world examples from global nonprofits, climate initiatives, and purpose-driven enterprises, illustrating how better data, not perfect data, is often the key to progress. The conversation also explores how by integrating sustainability, diversity, and social impact into AI as core infrastructure, businesses can create meaningful change that extends beyond profit.  Stay in touch with Julie:  Jessica Hammond on LinkedIn: https://www.linkedin.com/in/juliekae/  Qlik’s website: https://www.qlik.com/us  +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

As AI adoption accelerates, so do the risks. In this episode of The AI Forecast, Jessica Hammond—Senior Director Product Management of GenAI at Protegrity—joins host Paul Muller to unpack how organizations can move fast with AI without compromising security, privacy, or compliance. Drawing on her background in product, engineering, security, and compliance, Jessica explains why sensitive data exposure is one of the most underestimated risks in AI systems—from user-generated inputs leaking PII to agents inheriting permissions they shouldn’t have. She walks through how field-level data protection, policy-based controls, and governance embedded directly into the AI pipeline can protect data transparently, without slowing developers or re-architecting applications. The conversation also explores why governance can’t be bolted on at the end, how data protection impacts AI evaluations and non-deterministic outputs, and what it really takes to secure AI across hybrid and multi-cloud environments.  Stay in touch with Jessica:  Jessica Hammond on LinkedIn: https://www.linkedin.com/in/jessicalhammond/  +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

The AI Forecast welcomes back John Santaferraro, host of The Digital Analyst Podcast and CEO of Ferraro Consulting, for a candid  look at what’s really coming next for AI in 2026. John argues that despite nonstop headlines, most organizations are still dabbling with AI, not truly using the technology. He predicts that 2026 will be defined by AI literacy, strategic adoption, and a shift away from trivial use cases toward executive-level decision support. John and host Paul Muller explore why private AI will become essential for protecting intellectual property, how asking the right questions may soon matter more than having the right answers, and why agentic AI is poised to fail loudly before it succeeds. The discussion also dives into data and agent governance, the coming wave of platform and data unification, and why causal AI—not just GenAI—may unlock the next leap in predictive power.  If you’re planning your AI strategy for 2026, this conversation will help you separate signal from noise and prepare for what’s next. Stay in touch with John:  John Santaferraro on LinkedIn: https://www.linkedin.com/in/johnsantaferraro/  The Digital Analyst Podcast: https://www.youtube.com/playlist?list=PLivd8WaRu-XkJsuP8YAtk8T1QYRYlEkD5   Ferraro Consulting: https://www.ferraroconsulting.com/  +++ Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

In this episode of The AI Forecast, Anu Jain, founder and CEO of Nexus Cognitive, joins host Paul Muller to introduce a transformative idea: AI doesn’t have a last-mile problem. It has a first-mile problem. While AI models and algorithms can scale instantly through the cloud, their success still depends on the quality, provenance, and readiness of the data that feeds them. Drawing from his career spanning MicroStrategy, Deloitte, IBM Watson, Think Big Analytics, and now Nexus Cognitive, Anu explains why so many enterprise AI initiatives stall before production — not because of model complexity, but because data remains chaotic, siloed, and treated as an afterthought.  Anu explores the shift from data as “exhaust” to data as a strategic asset, the rise of composable architectures, and why he believes every piece of data needs a “digital birth certificate” to anchor trust, context, and lineage. Stay in touch with Anu: LinkedIn: https://www.linkedin.com/in/anujain/  Nexus Cognitive: https://www.nexuscognitive.com/  +++   Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

Cloudera Chief Marketing Officer Mary Wells helped spearhead the launch of Cloudera’s Women Leaders in Technology initiative, which recently celebrated its one-year anniversary. To honor this milestone, Mary joins this special edition of The AI Forecast to reflect on the impact of this program so far. Mary Wells and host Paul Muller embark on an inspiring conversation on leadership, allyship, and navigating one of the most transformative moments in technology. Mary reflects on more than three decades in the industry—spanning the rise of client/server, the dot-com boom, IoT, big data, and now the explosive acceleration of AI—and shares how each era shaped her leadership philosophy. She discusses why kindness is a strength, how to build teams rooted in trust and accountability, and why allyship—not exclusivity—is the secret to sustainable progress for women in tech. The two also dive into how AI is reshaping the marketing function, from generative content and personalization to the organizational change required to keep teams confident and empowered. Mary offers candid advice for CMOs navigating AI’s demands, and for leaders everywhere looking to build culture, resilience, and relevance in a world that’s moving faster than ever. To learn more about Cloudera’s Women Leaders in Technology, join the LinkedIn community and visit the home page. LinkedIn Community: https://www.linkedin.com/groups/13104138/  WLIT Website: https://www.cloudera.com/about/women-leaders-in-technology.html  And to stay in touch with Mary, follow her on LinkedIn: https://www.linkedin.com/in/maryhwells/    +++   Follow and subscribe to The AI Forecast for more conversations with the innovators shaping the future of enterprise AI.

GenAI may have captured the spotlight. But according to Dr. Jake Trippel, co-founder and CTO of Codename 37, the real disruption is still ahead. Jake joins the podcast to explain why today’s LLM-centric stacks will hit architectural limits and how “AI fabrics” and shared memory meshes can unlock agent-to-agent collaboration across data silos. From untangling decades of technical debt to the surprising move of model training back on-prem, Jake lays out pragmatic playbooks. He also shares how he runs “100 AI employees” today, what SaaS might look like in a bot-first world, and why education must embrace hyper-personalized learning while guarding against AI-enabled shortcuts. Stay in touch with Jake: LinkedIn: https://www.linkedin.com/in/jtrippel/  Codename 37: https://codename37.ai/    +++   Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.

Turning complex, siloed medical data into accessible, actionable insight isn’t just a technical challenge; it’s a human one.  In this episode of The AI Forecast, Luz Erez, physicist-turned-entrepreneur and CTO of MDClone, explores how synthetic data is transforming the way we use medical information for research, innovation, and patient care. Erez explains how MDClone’s platform manages tens of millions of patient records across hospitals worldwide—safely turning real data into synthetic datasets that preserve statistical accuracy while protecting privacy. He reveals how this breakthrough enables hospitals, researchers, and AI developers to collaborate without regulatory roadblocks, accelerating discoveries that can improve outcomes and reduce clinical workload. Stay in touch with Luz: LinkedIn: https://www.linkedin.com/in/erezsoft/    +++ Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.

Enterprise leaders are racing to deploy generative AI, but most overlook a critical foundation: data readiness. Despite bold ambitions, less than one-third of technology leaders believe their data is prepared to support AI at scale.  Marcela Vairo, IBM’s Vice President of Data and AI for the Americas, joins The AI Forecast to explore one of the most persistent challenges in enterprise AI: why strong data foundations remain the exception, not the rule. Drawing on more than 25 years at IBM, Marcela shares how organizations can close the gap between aspiration and execution through effective data governance, integration, and trust. She explains why governance isn’t a checkbox—it’s an enabler—and how companies can scale AI responsibly by building the right architecture, managing bias, and embracing data quality as a strategic asset.   Stay in touch with Marcela: LinkedIn: https://www.linkedin.com/in/marcela-vairo/    +++   Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.  

AI is transforming not only the way we work, but what we value as work. Success in this new era won’t come from chasing efficiency alone, but from cultivating cultures where AI empowers people, strengthens purpose, and drives innovation with trust at the center. In this episode of The AI Forecast, Teddra Burgess, founder of Chasing Outcomes, joins host Paul Muller to explore how AI is reshaping not just work, but what we value about work. Teddra lays out a practical path to building an “AI-anywhere” culture: start with outcomes (not tools), empower every function (not just IT), and lead with trust, purpose, and adaptability. Teddra shares how leaders can navigate uncertainty like a “navigator”—aligning people around a clear North Star while evolving skills, roles, and mindsets.  Stay in touch with Teddra: LinkedIn: https://www.linkedin.com/in/teddrathomasburgess/  +++ Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.

In this episode of The AI Forecast, Tom Harshbarger, Director of Cloud and AI Strategy at Arrow Electronics, joins host Paul Muller to unpack what it really takes to build enterprise AI solutions that deliver value. From navigating an immature market to choosing the right partners, Tom shares hard-earned lessons from decades in the industry on how to start small, experiment intelligently, and scale with confidence. They also explore why AI feels different from past technology waves, what makes today’s ecosystem uniquely complex, and how leaders can balance ambition with responsibility as the world races to integrate AI into every corner of business and life. Stay in touch with Tom: LinkedIn:https://www.linkedin.com/in/tom-harshbarger/  Arrow Electronics: arrow.com +++   Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.

The AI era is redefining what it takes to stay on top. Success won’t come from protecting the status quo, but from embracing the “always day one” mindset—where reinvention, adaptability, and bold experimentation drive progress.  Drawing on Big Tech’s playbook, Alex Kantrowitz, former journalist and now founder of Big Technology, joins host Paul Muller on The AI Forecast to discuss why continuous reinvention is the key to thriving in this new landscape, and how leaders can navigate AI’s impact on business, culture, and society. Stay in touch with Alex: LinkedIn: https://www.linkedin.com/in/alexkantrowitz/  Big Technology: https://www.bigtechnology.com/    +++   Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.  

What does it mean to design AI with humanity at its core? Jess Von Bank—futurist, HR transformation leader, and president of Diverse Daisies—joins The AI Forecast to discuss. With host Paul Muller, the two explore how AI is reshaping the workforce and our very sense of what it means to be human. From AI-driven recruiting and workforce redesign to the mental health crisis and the erosion of human connection, Jess challenges leaders to slow down, think deeply, and build technology that serves people, not replaces them. Stay in touch with Jess: LinkedIn: https://www.linkedin.com/in/jessvonbank/  +++   Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.

We’re entering a new era of Big Data defined by convergence—where on-premises and cloud systems come together to power trusted, private AI. By integrating AI with modern data architectures, organizations can harness the full value of their information, drive innovation, and enable a new wave of business outcomes in a rapidly evolving digital landscape. In this episode of The AI Forecast, Cloudera CTO Sergio Gago joins host Paul Muller to unpack the “third wave” of data and AI.  Plus, drawing on his experience as a musician, entrepreneur, and quantum computing leader, Sergio explores the creative and human dimensions of AI — from how music teaches us about data patterns to why the real value in AI lies in skills, context, and control. He shares his vision for a world where digital colleagues work alongside humans, how organizations can safely embrace AI agents, and why the future of business will depend on sovereign data and private intelligence. Stay in touch with Sergio: LinkedIn: https://www.linkedin.com/in/sergiogh  Sergio’s Quantum Pirates Newsletter: https://quantumpirates.substack.com/  +++ Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.

The future will not be decided by who experiments with AI first, but by who can operationalize it at scale - turning messy, fragmented data into trusted insights, deploying models seamlessly across hybrid environments, and delivering measurable business outcomes. To discuss, we’re joined by Patrick Moorhead, Founder, CEO and Chief Analyst at Moor Insights & Strategy.  He and host Paul Muller explore the importance of data quality, the impact of AI on various industries, and the need for effective data management strategies. Patrick shares insights from his extensive experience in technology and highlights the opportunities and challenges that AI presents for businesses today. Stay in touch with Patrick: LinkedIn: https://www.linkedin.com/in/patmoorhead/  Moor Insights & Strategy website: https://moorinsightsstrategy.com/    +++   Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.  

Fresh off his keynote at Cloudera’s EVOLVE NYC, futurist and author Mike Walsh returns to The AI Forecast to share bold insights on the rise of AI agents and what they mean for business, culture, and society. In this wide-ranging conversation, Mike explores how AI is evolving from simple automation into a limitless digital workforce, and why the real disruption lies in the second- and third-order consequences of this transformation. From model collapse and embodied AI to sovereign intelligence and the future of work, Mike challenges us to look beyond the hype and consider how AI will reshape organizations, economies, and even culture itself. Along the way, he reflects on his upcoming book, the risks of algorithmic echo chambers, and why now is the best time to be a creative thinker willing to embrace change. Stay in touch with Mike: LinkedIn: https://www.linkedin.com/in/michaelwalsh/  +++   Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast YouTube page.  

AI is changing the way businesses operate. But without trust, governance, and accountability, progress stalls.  Ojas Rege, SVP and GM of Privacy and Data Governance at OneTrust, joins The AI Forecast to explore how organizations can balance innovation with responsibility. He and host Paul Muller unpack why AI represents a “new class of risk,” what it means to design privacy and governance into systems from the very beginning, and how curiosity and context fuel better decision-making with data.  They also examine the shifting role of organizations as regulators sharpen their focus on AI, the need for new tooling to ensure explainability, and how human oversight will remain essential even as automation scales.   Stay in touch with Ojas:  Ojas on LinkedIn: https://www.linkedin.com/in/ojasrege     Like and subscribe to The AI Forecast to stay updated on the latest episodes. You can watch the video version of this episode on The AI Forecast. 

AI can’t transform businesses if organizations aren’t prepared to embrace it. Christian Lund, Co-Founder of Templafy, joins The AI Forecast to explore thoughtful AI deployment in an organization. He and host Paul Muller dive into the realities of today’s AI landscape—from why over 40% of AI projects are likely to be canceled, to the untapped potential of document workflows as a proving ground for successful adoption. They discuss how quality and context determine whether AI truly adds value, why trust is the indefinable ingredient in scaling AI, and how integrating tools into existing workflows can ease resistance. Christian also shares his perspective on finding “low-hanging fruit” projects that drive early wins, the transformative impact AI will have on knowledge workers, and why purposeful applications focused on ROI will define the future of AI in business. Stay in touch with Christian: Christian on LinkedIn: https://www.linkedin.com/in/christianlundcph/  +++ Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.

As part of our Women Leaders in Technology (WLIT) series on The AI Forecast, we’re joined by Avani Desai, CEO of Schellman, a leading cybersecurity firm. Each quarter, we’ll take a break from the regularly scheduled AI programming on The AI Forecast to direct our attention to this important topic in tech. Avani shares her journey from a curious kid in Orlando who loved to tinker with technology to becoming a leader in cybersecurity. She reflects on the pivotal moments that shaped her career, like her 15-year journey to accept vulnerability as a means of connection, not failure. She also shares how her leadership style—rooted in empathy, authenticity, and radical transparency (e.g., her “eye-to-eye with Desai” meetings with employees where no question is off limits)—has helped her build trust, inspire teams, and drive innovation.  To learn more about Cloudera’s Women Leaders in Technology, join the LinkedIn community and visit the home page. LinkedIn Community: https://www.linkedin.com/groups/13104138/  WLIT Website: https://www.cloudera.com/about/women-leaders-in-technology.html  And to stay in touch with Avani, follow her on LinkedIn: https://www.linkedin.com/in/avanimehtadesai/ 

AI can’t transform businesses if organizations aren’t prepared to embrace it.  Donna Beasley, Chief AI Enablement Officer, joins The AI Forecast to explore thoughtful AI deployment in an organization. She and host Paul Muller dive into the challenges and opportunities of AI adoption, from ensuring data quality to driving organizational change management.  They discuss the importance of collaboration across departments, strategies for overcoming resistance, and the critical role of training and meeting individuals where they are in their openness with AI.   Stay in touch with Donna:   Donna on LinkedIn: https://www.linkedin.com/in/donna-beasley04349/     Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.

A city can’t be smart if its systems don’t serve its citizens. Ayesha Khanna, AI advisor, entrepreneur, and CEO of Addo, joins The AI Forecast to explore how AI is reshaping the cities we live in and the lives we lead within them. She and host Paul Muller dive into the intersection of AI and urban development, where infrastructure, governance, and personalization come together to elevate the quality of life. They discuss the real-world challenges of deploying innovative city technologies, the critical role of data management, and how AI can expand access to services like education and healthcare. She also shares her journey as a technologist, her work empowering women in the industry, and why ethical, human-centered design must guide the future of AI-powered cities. Stay in touch with Ayesha:  Ayesha on LinkedIn: https://www.linkedin.com/in/ayeshakhanna/    Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.

When AI needs to think faster, the architecture beneath it matters more than ever. Val Cook, Chief Software Architect at Blaize, joins The AI Forecast to unpack how today’s AI systems demand more than raw compute, but more adaptable infrastructure. He and host Paul Muller explore the critical intersection of hardware and software, the growing importance of data flow machines, and the limits of traditional architectures in real-time environments. They examine the emerging hybrid approach to AI, balancing centralized and Edge computing, and why dynamic use cases require systems that can react in the moment. Cook also emphasizes that innovation, not scale alone, will define the future of AI and that the teams that rethink the foundation will build what’s next. Stay in touch with Val: Val on LinkedIn: https://www.linkedin.com/in/val-cook-5a552520/   Like and subscribe to The AI Forecast to stay updated on the latest episodes. You can watch the video version of this episode on The AI Forecast.

When trust collapses, everything else goes with it.  Jim Brennan, Chief Product and Technical Officer at GetReal Security, joins The AI Forecast to break down one of the biggest challenges in today’s world: securing digital trust. He and host Paul Muller explore why trust is the backbone of modern business and how advancements like deepfakes, impersonation attacks, and AI-powered deception are shaking that foundation They discuss why digital trust is forged through signals like signatures and interactions, how its erosion can trigger real business fallout, and what it takes to fight back. Stay in touch with Jim: Jim on LinkedIn: https://www.linkedin.com/in/jibrennan/ Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.

As AI systems grow more powerful, so does a more profound structural concern: ownership. A handful of players now control the data, infrastructure, and models shaping global AI and, with them, the rules of access, participation, and innovation. Sean Ren, co-founder of Sahara AI, joins The AI Forecast to explore the implications of competition in the AI industry, the necessity of decentralized technology, and the challenges of data ownership. Sean shares the potential for decentralized AI to disrupt existing economic models, the risks of centralized AI for businesses, and the future of knowledge workers in an AI-driven world. Stay in touch with Sean:  Sean on LinkedIn: https://www.linkedin.com/in/xren7/  Sahara AI: https://saharaai.com/    Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.

Jim Liddle, Chief Innovation Officer of Data Intelligence and AI at Nasuni, joins The AI Forecast to spotlight a critical obstacle to enterprise AI: messy, ungoverned data. He and host Paul Muller trace the evolution of data management and unpack why so many organizations still struggle with the basics, starting with the challenge of taming unstructured information. They explore how the absence of a unified data foundation blocks progress, how poor taxonomy erodes trust in AI, and why critical thinking, not just compute, is the missing piece in most AI strategies. Jim also looks ahead to the future of AI, tackling emerging concerns from algorithmic bias to the geopolitical implications of intelligent systems. Because in the end, if your data’s not ready, your AI won’t be either.   Stay in touch with Jim: Jim on LinkedIn: https://www.linkedin.com/in/jimliddle/  +++ Like and subscribe to The AI Forecast to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.