The AI Forecast: Data and AI in the Cloud Era

Cloudera

The introduction of the first computer. The boom of the dotcom renaissance. Now, the dawn of AI. The throughline across each of these momentous inflections in our digital lives has been data. But the presence of data doesn’t mean immediate insights and results. It’s the architectures and systems in place that determine the true value—and trust—of data. In this podcast by Cloudera, The AI Forecast: Data and AI in the Cloud Era explores the past, present, and future of enterprise AI with today’s leading companies and industry experts. You don’t want to miss this.

  1. 4d ago

    Enterprise AI Success: What Separates Results from Expensive Experiments

    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.

  2. Aug 5

    How AI Is Helping Humanitarian Teams Make Faster Decisions

    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.

  3. Jul 29

    From KPIs to Action: What Comes After The Dashboard?

    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.

  4. Jul 22

    Behavior Change: How Startups Are Making AI Stick

    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.

  5. Jul 15

    AI Guardrails: How to Govern AI Without Slowing Innovation

    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.

  6. Jul 8

    Decision Logic: The Difference Between an Answer and a Decision

    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.

  7. Jun 24

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

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

  8. Jun 17

    Mastering Enterprise AI: Why Some Projects Succeed While Others Fail

    AI may be the most capable intern your organization has ever hired. However, interns still need guidance and clear direction. Enterprise AI is proving no different. In this episode of The AI Forecast, Paul Muller sits down with Michael Gray, CTO of Thrive, to explore the patterns and anti-patterns emerging from real-world enterprise AI deployments.  Drawing on his experience helping organizations implement AI at scale, Michael offers a practical framework for evaluating AI maturity, helping leaders understand where adoption breaks down and what it takes to build momentum across the organization.  Paul and Michael take a closer look at: Why AI adoption often stalls despite significant technology investments The role of organizational change management in successful AI programs Common AI adoption patterns and anti-patterns across enterprises How champions inside the organization can accelerate AI success How governance and security evolve as AI scales The importance of focusing on business outcomes rather than technology alone The path from AI investment to business value is often more complex than expected. This episode offers advice on turning AI investments into measurable outcomes while building the organizational foundations for successful scaling.  To hear more about the organizational challenges facing AI adoption, check out Ep 69 | Industrial Enterprise AI: Growing Value and Organizational Risk Management  Stay in touch with Michael: Michael Gray on LinkedIn: https://www.linkedin.com/in/michael-gray-4861663/ +++ Like and subscribe to The AI Forecast, sponsored by Cloudera, to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.

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The introduction of the first computer. The boom of the dotcom renaissance. Now, the dawn of AI. The throughline across each of these momentous inflections in our digital lives has been data. But the presence of data doesn’t mean immediate insights and results. It’s the architectures and systems in place that determine the true value—and trust—of data. In this podcast by Cloudera, The AI Forecast: Data and AI in the Cloud Era explores the past, present, and future of enterprise AI with today’s leading companies and industry experts. You don’t want to miss this.

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