The AI with Maribel Lopez (AI with ML)

Maribel Lopez

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. 

  1. Physics AI Explained: Why Hardware Design Requires a Different Kind of AI

    19H AGO

    Physics AI Explained: Why Hardware Design Requires a Different Kind of AI

    Not every AI problem is a language problem. I talk with Vinci CEO Hardik Kabaria about what changes when AI has to reason about the physical world. Full show notes Most of the AI conversation in enterprise circles is about large language models — text, code, maybe images. This episode is about something different: what happens when AI has to reason about physical systems where the laws of physics don't negotiate and a wrong answer can't be patched after the product ships. I talked with Hardik Kabaria, CEO of Vinci, about how physics-based AI models are built differently from generative models, why determinism is a requirement rather than a preference in hardware design, and what it means for organizations manufacturing physical products to think carefully about where AI fits in their workflow. The conversation covers data security, scalability, and the practical question of how to evaluate new AI tools when the cost of a mistake is measured in product recalls rather than content edits. This episode is most relevant for technology leaders at companies that design or manufacture physical products. But the underlying insight — that deterministic and probabilistic AI serve different purposes and require different evaluation criteria — applies to any organization building a portfolio of AI tools. What we cover: Why physics-based AI is a different modality than large language models, and what that means for how you build and evaluate itThe case for determinism in AI: why hardware design requires the same answer every time, regardless of who asksHow AI is making physics analysis accessible to more engineers, reducing dependence on a small pool of highly specialized talentWhy data security requirements are higher for hardware design than for most enterprise AI deployments — and what deployment models address thatHow to think about AI across the full product lifecycle, from early concept to manufacturing sign-offWhat "trust but verify" looks like in practice: building benchmarks before deploying AI in high-stakes design workflowsTimestamps: Chapters: 00:00 Introduction to AI and Vinci 02:04 Understanding Physics Intelligence Layer 04:20 The Role of Physics in AI Models 07:04 Digital Twins and AI Scalability 09:35 Misconceptions in AI for Physical Systems 12:15 Determinism vs. Non-Determinism in AI 15:01 Deployment Challenges for Physics-Based AI 17:41 Signals of Success in AI Implementation 20:20 The Future of AI in Hardware Design 23:01 Preparing for the Shift to AI in Physical Systems Guest bio Hardik Kabaria is CEO and co-founder of Vinci, an AI company building foundation models for the physical world. His background is in physics and geometry software for hardware engineering, with experience across the tools mechanical and electrical engineers use to design, simulate, and manufacture physical components. Vinci was founded two and a half years ago and is focused on making physics-based analysis accessible at the speed and scale of AI inference. Company: VinciResources mentioned: Vinci:  https://www.getvinci.aiLopez Research blog: https://www.lopezresearch.com/research/📢 STAY CONNECTED Subscribe 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.lopez

    28 min

  2. 6D AGO

    NemoClaw, OpenClaw, and the Real Reason Enterprises Haven’t Deployed AI Agents Yet

    NVIDIA’s NemoClaw adds enterprise security to OpenClaw. What it does, what it doesn’t, and what CIOs should do before deploying. FULL SHOW NOTES OpenClaw became the fastest-growing open-source project in history. Enterprise buyers watched from the sidelines — not because the technology wasn’t useful, but because an autonomous agent with access to corporate file systems, credentials, and external communication channels is a governance and security problem that no one had solved at the enterprise level. At NVIDIA’s GTC 2026 conference, Jensen Huang announced NemoClaw: a reference stack that adds enterprise security controls to OpenClaw. In this solo episode, Maribel Lopez breaks down what NemoClaw actually does, why the SaaS partner ecosystem matters as much as the technology itself, and where the hype is running ahead of the reality. WHAT WE COVER •       Why OpenClaw created a shadow IT problem before NemoClaw existed •       What OpenShell, the Privacy Router, and Nemotron models actually do for enterprise buyers •       Why Salesforce, ServiceNow, SAP, Cisco, and CrowdStrike being in the ecosystem matters •       The hardware dependency NVIDIA’s marketing glosses over •       Why “working with NVIDIA” and “ready to deploy” are not the same thing •       The three questions every CIO should answer before touching any of this   TIMESTAMPS 00:00  —  Why enterprise IT teams were watching OpenClaw from the sidelines 01:45  —  What OpenClaw is and why it created an enterprise security problem 04:00  —  What NemoClaw actually does: OpenShell, Privacy Router, Nemotron 06:30  —  The SaaS ecosystem: Salesforce, ServiceNow, SAP, Cisco, CrowdStrike 08:30  —  Where the hype is ahead of the reality 10:15  —  Three questions CIOs should answer before deploying RESOURCES MENTIONED •       NemoClaw announcement and NVIDIA Agent Toolkit: build.nvidia.com •       Full written analysis: NemoClaw Brings Enterprise-Grade Security Controls to OpenClaw — lopezresearch.com •       NVIDIA GTC 2026 Jensen Huang keynote ABOUT THIS PODCAST AI with Maribel Lopez covers enterprise AI adoption, agentic systems, AI governance, and AI-driven customer experience. Maribel Lopez is founder and principal analyst at Lopez Research, a technology research and strategy firm. Subscribe on Apple Podcasts, Spotify, or your platform of choice. KEYWORDS enterprise AI agents, agentic AI security, NemoClaw NVIDIA, OpenClaw enterprise deployment, AI agent governance, enterprise AI strategy, AI governance enterprise, agentic AI risks

    16 min

  3. MAR 10

    Why Deploying More AI Tools Won’t Fix Your Workflows: Lessons Learned From Cisco

    Most enterprises are layering AI tools on top of broken processes and wondering why ROI never materializes. In this solo episode, Maribel breaks down Cisco’s systematic approach to workflow redesign, why visibility into how work actually gets done is the missing first step, and what enterprise leaders need to change about their leadership culture and talent systems before AI adoption will deliver real results. Key Topics Covered •  Why AI tool adoption without workflow redesign fails to deliver ROI •  How Cisco’s Atlas AI agent system maps work across the enterprise •  The digital workflow canvas that lets leaders redesign processes systematically •  Results from Cisco’s pilot: 60% of activities AI-augmentable, 28 transformational use cases • Why framing AI as augmentation rather than headcount reduction drives adoption •  The leadership and talent system changes most companies miss Key Takeaway The technology exists. The use cases are proven. What’s missing is the organizational discipline to redesign workflows before deploying more tools. Start with your data and your processes, not your tools. Resources & Links  Blog post: Why AI Tool Adoption Without Workflow Redesign Is a Waste of Money [Lopez Research]  Related: Five Steps to Follow for Successful AI Deployments [Lopez Research] Related: Three Shifts in AI-Driven Labor That CIOs and CEOs Can’t Ignore [Lopez Research] Subscribe to AI with Maribel Lopez on your channel of choice here.

    11 min

  4. MAR 3

    SaaS Isn't Dead — But the "Dead" Narrative Is Leading Enterprise Buyers Astray

    Episode Summary: The "SaaS is dead" narrative is generating real confusion for enterprise buyers trying to make procurement decisions right now. In this solo episode, Maribel Lopez breaks down the two legitimate arguments driving the disruption narrative — AI coding tools and agentic AI — separates what's real from what's overstated, and gives enterprise technology leaders the two questions that actually matter for evaluating their SaaS stack in an AI-first world. What You'll Learn: Why AI coding tools like Claude Code and Codex are not a SaaS replacement strategy — and what they should be used for insteadWhere agentic AI creates genuine revenue model pressure for SaaS vendors, and which vendors are already respondingThe specific conditions that would have to be true for SaaS to decline significantly — and which are not yet metHow to evaluate your SaaS vendors' agentic AI readiness beyond roadmap promisesWhy the liability and compliance math still heavily favors established SaaS platforms for most enterprise use casesKey Takeaways: Rebuilding mature systems of record with AI coding tools is not a competitive advantage — it's a distraction from building software that reflects your actual differentiationThe per-seat revenue model is under real pressure, but vendors moving on agentic capabilities are finding new revenue: Salesforce is generating $540M ARR from AgentForce; Intercom crossed $200M from its AI-first pivotCommodity SaaS with no data moat or compliance depth faces the hardest disruption; platforms with systems of record have a path forwardThe right test for any SaaS vendor right now: what can they show you working in production — not a roadmap, not a demoCompanies and Examples Referenced: Salesforce / AgentForce: $540M ARR from agentic capabilitiesIntercom: $200M ARR from AI-first product pivotWorkday: Certified connector ecosystem as an example of integration moats that can't be replicated quicklySAP: Proactive procurement optimization as an example of SaaS becoming more valuable, not lessResources: Read the full article: SaaS Isn't Dead. But Its Revenue Model Is Under Pressure — Lopez ResearchReferenced: Cathay Capital on agentic AI and B2B softwareConnect with Maribel on LinkedInSubscribe to AI with Maribel Lopez on your podcast channel of choice — links at lopezresearch.com. SEO Keywords: enterprise AI adoption, SaaS revenue model, agentic AI enterprise, AI agents B2B software, enterprise software evaluation, AI coding tools enterprise, SaaS disruption, enterprise AI strategy

    13 min

  5. FEB 24

    Agentic AI Beyond the Hype: How Banks Are Actually Deploying It

    Keywords AI, agentic AI, Work Fusion, RPA, intelligent automation, compliance, machine learning, LLMs, automation, enterprise technology Episode Summary Agentic AI dominated industry conversation in 2025. But in 2026, enterprise leaders are asking a harder question: How do we deploy AI agents safely, accurately, and in production environments? In this episode, Maribel Lopez speaks with Peter Cousins, CTO of WorkFusion a UiPath company, about how AI agents evolved from RPA and intelligent automation into production-ready “digital workers.” The discussion focuses on regulated industries, where explainability, auditability, and risk controls matter as much as automation gains. Rather than hype, this conversation explores what it takes to operationalize AI agents: governance frameworks, confidence thresholds, human oversight, and model risk management. Sound Bites "2025 was the big agentic AI year.""You can't just throw it in and it's good to go.""It's been great talking to you."Chapters 00:00 Introduction to Agentic AI and Work Fusion 02:00 Transitioning from RPA to AI Agents 04:38 Operationalizing AI Agents in Business 09:21 Navigating the Hype of Agentic AI 12:04 The Role of LLMs in Regulated Environments 14:47 Multi-Agent Orchestration and Collaboration 17:21 Improving AI Agents through Learning 21:01 The Importance of Non-Human Identity in AI 24:06 Closing Thoughts on Adopting Agentic AI

    24 min

  6. FEB 17

    Agentic Commerce QuickTake: Should Anyone Care?

    The National Retail Federation Show highlighted that Agentic Commerce is the new buzzword for 2026. But before you rewrite your roadmap, let's talk reality. Julie Ask and Maribel Lopez are discussing: What actually has to happen before agents can buy things for consumers Why 85% of retail is still offline (and what that means for AI commerce) The payments protocol wars: Google/Shopify vs. OpenAI/Stripe/PayPal Where to actually invest your AI budget in customer experience Spoiler: The "auto-magic" future isn't here yet. But the opportunities in between?   #AgenticAI #RetailInnovation #CommerceAI #NRF2026

    16 min

  7. JAN 21

    AI, CX, and the Shift from Automation to Action with Jarrod Johnson of TaskUs

    Agentic AI is emerging as the next evolution of artificial intelligence in customer experience (CX), moving beyond chatbots to systems that can take real action on behalf of customers. In this episode of AI with Maribel Lopez, Maribel Lopez speaks with Jarrod Johnson, Chief Customer Officer at TaskUs, about how enterprises are actually deploying AI in customer experience today. The conversation covers real-world CX use cases, where AI delivers measurable ROI, why data and process design remain the biggest bottlenecks, and how organizations should manage risk, governance, and human handoffs as agentic AI scales. This episode is designed for enterprise leaders evaluating AI strategies for customer experience transformation. Bio: Jarrod Johnson, Chief Customer Officer, TaskUs Jarrod Johnson is the Chief Customer Officer of TaskUs. He is responsible for TaskUs' go-to-market strategy and execution across all client-facing and market-facing functions. Jarrod leads the "Client Organization" at TaskUs, including client success, sales, product and service management, and TaskUs’ consulting function, which includes the Agentic AI Consulting Practice. Jarrod is responsible for all aspects of revenue management and growth for TaskUs. He brings over 20 years of experience in enterprise technology-enabled services and business management. Show notes 00:00 – AI in Customer Experience (CX): What This Episode Covers 01:31 – What a Chief Customer Officer Does in AI-Driven Customer Experience 03:46 – Top Customer Experience (CX) Bottlenecks Blocking AI Adoption 05:56 – Chatbots vs. Agentic AI: What’s the Difference in Customer Experience? 09:31 – How to Start with Agentic AI in Customer Experience (Real ROI Use Cases) 12:46 – When AI Should Hand Off to Humans in Customer Experience 15:41 – AI in Customer Experience: Cost Reduction vs. Revenue Growth 18:21 – Voice AI in Customer Service: Why It Finally Works 22:01 – AI Guardrails, Safety, and Brand Risk in Customer Experience 26:31 – Measuring AI-Driven Customer Experience (CX Metrics That Matter) 29:46 – AI for Customer Experience: Market Fragmentation and Vendor Landscape 33:46 – Agentic AI Pitfalls to Avoid in Customer Experience Transformation

    37 min

  8. JAN 13

    CES Quick Take Part 1: Julie Ask of Ask Advisory

    CES 2026 Quick Take: Physical AI, Ambient AI, and the Reality of Adoption In this episode, Maribel Lopez, founder and principal analyst at Lopez Research, is joined by Julie Ask, founder of Ask Advisory, for a candid, unscripted conversation on what CES 2026 actually revealed about the state of AI. Rather than focusing on flashy demos or speculative promises, Maribel and Julie examine where AI is delivering real value today—and where expectations are running ahead of reality.  Julie's bio Julie is a prominent customer experience analyst, technology futurist, and digital product strategist who has advised hundreds of global brands on the impact emerging technologies (e.g., mobile, sensors, extended reality, networks, AI) can and will have on customer experiences. She actively works with enterprises and vendors to understand how technology and consumer trends will impact their business with a deep focus on customer engagement strategies.  For more than 25 years, her work has defined the evolution of consumer digital experiences and inspired brands to take action. Her combined background in engineering and business gives her a unique ability to help business leaders understand what is possible and leverage technology to drive business outcomes. She has appeared frequently on Bloomberg while her research has been cited by the Wall Street Journal, New York Times, Financial Times, and a breadth of marketing publications. She co-authored The Mobile Mind Shift book in 2014. She founded Julie Ask Advisory in 2024 to pursue her passion for helping business leaders understand the impact of AI on experiences.

    9 min
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5
out of 5
21 Ratings

About

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. 

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