『The AI with Maribel Lopez (AI with ML)』のカバーアート

The AI with Maribel Lopez (AI with ML)

The AI with Maribel Lopez (AI with ML)

著者： Maribel Lopez
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The AI with Maribel Lopez podcast interviews leading thinkers, experts and innovators on the latest trends in Artificial intelligence areas such as agentic AI, generative AI, AI security, AI ethics and governance. Maribel Lopez is a technology industry analyst, keynote speaker and founder of the Data For Betterment Foundation and Lopez Research. The podcast shares advice, strategies and techniques on how to use AI solutions such as conversational AI, computer vision and automation to make businesses more efficient. New episodes are released every week on Wednesdays.

© 2026 The AI with Maribel Lopez (AI with ML) 数学 科学
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  • Why Traditional IAM Breaks Down in the Age of Agentic AI

    Why Traditional IAM Breaks Down in the Age of Agentic AI
    2026/08/25


    In this episode, Jo Peterson, of Cleartech Research, discusses AI security challenges with Maribel Lopez. Her commentary explores how traditional security tools fall short for AI agents and what strategies enterprises can adopt to manage AI risks effectively.

    Topics covered

    • AI security challenges and solutions
    • Multi-layered approach to AI agent security
    • Token cryptographic delegation and OBO tokens
    • Externalized policy as code and micro-segmentation
    • Contextual and data-aware guardrails
    • Continuous auditing and behavioral baselines
    • Role of Chief AI Officer in security governance
    • AI risk management and operational strategies

    Key takeaways

    • Traditional security tools are not designed for AI agents and their non-deterministic behavior.
    • Implementing least privilege for AI agents involves multi-layered strategies including token delegation and policy enforcement.
    • Externalizing authorization to decoupled policy decision points enhances security for AI workflows.
    • Real-time observability and kill switches are critical for managing AI agent behavior.
    • Many organizations claim to have AI governance but lack technical implementation and operational ownership.


    Chapters

    00:00 Introduction to AI security challenges
    02:04 Non-deterministic nature of AI and security implications
    04:32 Externalized policy as code and micro-segmentation
    07:12 Real-time observability and kill switches
    09:11 Effectiveness of AI governance in organizations
    12:13 Immediate actions for AI security in 30 days
    13:45 Centralized AI traffic interception and inventory
    14:29 Role of Chief AI Officer in security and risk
    16:19 The evolving role of AI leadership in organizations
    17:19 Talent acquisition and upskilling for AI security



    STAY CONNECTED

    • Subscribe to the AI with Maribel Lopez audio podcast: https://www.buzzsprout.com/1947446
    • Subscribe to my LinkedIn newsletter — AI Decoded with Maribel Lopez: https://www.linkedin.com/newsletters/ai-decoded-with-maribel-lopez-7312533413582827520/
    • Lopez Research blog: https://www.lopezresearch.com/research/
    • Follow me on LinkedIn: https://www.linkedin.com/in/maribellopez/
    • Follow me on X: https://x.com/MaribelLopez
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    21 分
  • Beyond the Box Score: AI in Sports with Jono Luk of Sumer Sports

    Beyond the Box Score: AI in Sports with Jono Luk of Sumer Sports
    2026/08/10
    Football franchises run on data. Jono Luk of Sumer Sports explains how AI is changing who wins — on the field and in the stands.Full Show Notes:Most sports AI coverage focuses on stats. Jono Luk, Chief Product Officer at Sumer Sports, is thinking about something harder: measuring what a player decided, not just what they did. Sumer's computer vision tracks all 22 players up to 60 times per second, generating probabilities for every moment of every play — not to describe what happened, but to evaluate whether the best decision was made.That depth of game intelligence turns out to be useful in two places. For coaches, GMs, and scouts, it surfaces skill that box scores miss entirely. For the business side of a franchise, that same real-time game data becomes the trigger for personalized fan experiences — the right offer, the right moment, whether someone is in the stadium or watching from a sports bar. Jono calls this the before, during, and after — and argues it's the same attract-retain-monetize cycle every enterprise runs, just with a different playbook.The episode also covers what Jono wishes organizations understood before they start any AI conversation: AI isn't synonymous with LLMs. Computer vision, specialized models, and multi-component pipelines built for specific data types are doing work that frontier models simply aren't designed for. That framing matters for any enterprise buyer, not just sports franchises.What We Cover:How Sumer Sports uses computer vision to evaluate player decisions, not just outcomesWhy specialized AI models outperform general-purpose frontier models for sports analyticsThe two sides of AI in a football franchise: football operations and fan engagementHow real-time game data triggers personalized in-venue and at-home fan experiencesWhat the NIL era means for AI-assisted recruiting at college and high school levelsWhy AI in the enterprise isn't just about LLMs — and how to think about the broader toolkitThe one question Jono wants every organization to ask before deploying AIGuest Bio:Jono Luk is Chief Product Officer at Sumer Sports, a football data analytics and AI company that uses computer vision to analyze every player, every game, in real time. Before Sumer, Jono held product and technology leadership roles at Cisco. He brings a cross-industry perspective on how AI fits into larger solutions — not as a replacement for human judgment, but as the infrastructure that surfaces better decisions faster.Sumer Sports: https://www.sumersports.comJono Luk on LinkedIn: https://www.linkedin.com/in/jonoluk/ (confirm URL before publishing)Resources Mentioned:Sumer Sports: https://www.sumersports.comLopez Research: https://www.lopezresearch.com/research/📢 STAY CONNECTEDSubscribe to the AI with Maribel Lopez audio podcast: https://www.buzzsprout.com/1947446Subscribe to my LinkedIn newsletter — AI Decoded with Maribel Lopez: https://www.linkedin.com/newsletters/ai-decoded-with-maribel-lopez-7312533413582827520/Lopez Research blog: https://www.lopezresearch.com/research/Follow me on LinkedIn: https://www.linkedin.com/in/maribellopez/Follow me on X: https://x.com/MaribelLopez🔍 ABOUT MARIBEL LOPEZMaribel Lopez is founder and principal analyst at Lopez Research, a technology research and strategy firm focused on enterprise AI. She advises CIOs, CDOs, CMOs, IT leaders and technology vendors on AI adoption, agentic systems, AI governance, and AI-driven customer experience. Her insights have been featured in mainstream TV and print media such as Bloomberg, CGTN, Marketwatch, Reuters, Wall Street Journal, and Yahoo Finance. She's also a contributor to Forbes.com, and her research is used by organizations navigating the gap between AI capability and enterprise deployment reality.SEO Keywords:Sumer Sports, Jono Luk, sports AI analytics, football analytics AI, AI fan engagement, computer vision sports, AI recruiting sports, NIL technology, specialized AI models, enterprise AI adoption, vertical AI, AI for business outcomes, AI strategy enterprise, physical AI, Maribel Lopez, Lopez Research, AI with Maribel Lopez STAY CONNECTEDSubscribe to the AI with Maribel Lopez audio podcast: https://www.buzzsprout.com/1947446Subscribe to my LinkedIn newsletter — AI Decoded with Maribel Lopez: https://www.linkedin.com/newsletters/ai-decoded-with-maribel-lopez-7312533413582827520/Lopez Research blog: https://www.lopezresearch.com/research/Follow me on LinkedIn: https://www.linkedin.com/in/maribellopez/Follow me on X: https://x.com/MaribelLopez
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    26 分
  • Neeraj Verma of NiCE on What Separates AI Pilots From Production

    Neeraj Verma of NiCE on What Separates AI Pilots From Production
    2026/08/04

    Neeraj Verma of NiCE on why AI pilots stall, building agents as small reusable units, and the scale problem personal agents are about to create.

    Full show notes
    This one was recorded live at NiCE World 2026 in Orlando, and Neeraj Verma, Head of AI at NiCE, didn't dodge the hard parts. We started where most enterprise AI conversations should start and rarely do: the outcome. If you can't name what the technology is supposed to pay you back for, you're experimenting for experimentation's sake, and that's the pattern I see stalling pilots everywhere.

    From there we got into the fast-moving stuff — what an agent actually is, where skills fit, and why the smart move is building small, reusable units of work rather than monolithic agents. Neeraj made a point I keep thinking about: agents aren't humans, they're context engines, and they need small context to execute well. We also dug into guardrails and observability, and the real tension there — you have to have them, but not in a way that doubles your cost or ruins the experience.

    If you're a technology leader trying to move from pilot to production, or a CX leader watching personal agents start to change what "scale" even means, this is worth your time. The honest through-line: this wave will move faster than any before it, and it still takes real infrastructure and a continuous-innovation mindset to get right.

    What we cover

    • Why an outcome has to come before the AI build
    • What an AI agent is, and how skills package tools and processes
    • Building small, reusable, modular units of work for agents
    • Context as compressed enterprise data — and why compression is the hard problem
    • Harness engineering, and "agentic whack-a-mole"
    • Compounding intelligence and what self-learning really means today
    • Personal agents, agent-to-agent communication, and the coming scale problem
    • Guardrails, observability, and keeping shadow AI in check


    STAY CONNECTED

    • Subscribe to the AI with Maribel Lopez audio podcast: https://www.buzzsprout.com/1947446
    • Subscribe to my LinkedIn newsletter — AI Decoded with Maribel Lopez: https://www.linkedin.com/newsletters/ai-decoded-with-maribel-lopez-7312533413582827520/
    • Lopez Research blog: https://www.lopezresearch.com/research/
    • Follow me on LinkedIn: https://www.linkedin.com/in/maribellopez/
    • Follow me on X: https://x.com/MaribelLopez
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    22 分
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