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Earley AI Podcast

Earley AI Podcast

De : Seth Earley
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In this podcast hosts Seth Earley invites a broad array of thought leaders and practitioners to talk about what's possible in artificial intelligence as well as what is practical in the space as we move toward a world where AI is embedded in all aspects of our personal and professional lives. They explore what's emerging in technology, data science, and enterprise applications for artificial intelligence and machine learning and how to get from early-stage AI projects to fully mature applications. Seth is founder & CEO of Earley Information Science and the award-winning author of "The AI Powered Enterprise."

© 2026 Earley AI Podcast
Economie
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  • The Adults in the AI Room – Episode 102: AI in the Contact Center, Why Implementations Fail, and the Business Model Reckoning with Michael Darwal
    Nov 5 2026
    What if the real promise of AI in the contact center isn’t replacing human agents, but making every conversation faster, smarter, and more likely to end in a real resolution?The Adults in the AI Room (formerly the Earley AI Podcast) — On this podcast, host Seth Earley invites Michael Darwal, Chief AI and Digital Officer at ibex, for a practical conversation about AI agents, customer journey mapping, cost-per-resolution pricing, workforce development, and the knowledge foundations that decide whether contact center AI succeeds.When generative AI arrived, many predicted it would quickly automate away 70% or more of traditional call center work. The reality has been far more nuanced. Studies now suggest that roughly 95% of AI implementations fail to deliver the ROI they promised, often because organizations misunderstand what AI can do, where it fits in the customer journey, and how success should be measured.Michael explains why treating AI as a binary choice, where either the AI handles the call or a human does, sets companies up to fail. The better approach is a spectrum. In it, AI agents take on simpler interactions and handle the front end of complex calls, then hand off verified, summarized information to human agents who can resolve the issue faster.He also shares how ibex combines best-in-class conversational AI technology from partner Sierra AI with decades of customer journey data. That pairing lets ibex map interactions, set realistic expectations, and launch AI agents in digestible stages rather than trying to boil the ocean.In this episode, you’ll discover:Why most AI implementations in the contact center fail to deliver their promised ROIWhy the “AI or human” framing leads companies to measure the wrong thingsHow to define success across customer satisfaction, ROI, and first-contact resolutionWhy automating every cancellation request can quietly hurt the businessHow AI agents can cut a 20-minute call by 40% to 50% without handling it aloneWhy historical customer journey data is the foundation of a successful AI deploymentHow to identify which 30% of call volume is easiest to automate firstWhy replacing the traditional IVR menu with an AI agent is often a smart starting pointHow the contact center pricing model is shifting from cost per hour to cost per resolutionWhy cost-per-resolution models can deliver savings of 50% or more for clientsHow AI is helping ibex capture market share instead of shrinking revenueHow AI tools increased human agent throughput by 40%Why AI is making contact center jobs more enjoyable and improving retentionWhere the next generation of experienced contact center leaders will come fromHow AI is helping build better knowledge bases faster from disparate legacy systemsMichael brings 13 years of experience at ibex, a global customer experience management company with nearly 40,000 employees operating 31 contact centers. Its locations span the U.S., Jamaica, Nicaragua, Honduras, the Philippines, Pakistan, and India. His career at the company has moved across finance, digital marketing, and now AI, where he leads the development of the Wave iX platform for integrating AI agents into traditional customer experience workflows.He also shares how AI tools have changed the employee experience at ibex. They have helped the company recruit from a wider talent pool, get new agents to proficiency faster, and raise its employee NPS from an already high 77 to 82.Michael explains why the company’s strongest AI ideas often come from people who started their careers on the phones. Many ibex leaders have risen from agent to supervisor, floor manager, director, and even country manager. Those firsthand experiences continue to shape how the company builds and improves its AI agent lifecycle.His message is simple but powerful: AI succeeds in the contact center when it is built around the real customer journey, measured by true resolution, and designed to make both customers and human agents more effective.The Adults in the AI Room explores what it takes to make AI work inside the large enterprise, from the pilot to production. Each episode features leaders, builders, researchers, and practitioners who have put AI to work and can speak to real results. If you’re a CX leader, contact center executive, Chief AI Officer, operations leader, or enterprise technology decision-maker, this podcast is built to provide practical lessons you can apply.🎙️ Listen to the full episode and discover how AI agents and human agents can work together to deliver faster resolutions, lower costs, and better customer experiences.About The Adults in the AI RoomHosted by Seth Earley, The Adults in the AI Room features conversations with the leaders, builders, researchers, and practitioners who have taken AI from pilot to production inside the enterprise.Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-homeApple Podcast: https://podcasts.apple.com/us/podcast/...
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    21 min
  • Earley AI Podcast – Episode 101: IoT and OT Security, How AI Erased Security Through Obscurity, and What Organizations Need to Do Now with John Gallagher
    Sep 28 2026

    Why the Physical World Is Now the Biggest Cybersecurity Vulnerability in Most Organizations - and Why AI Changed Everything

    Guest: John Gallagher, VP Viakoo Labs at Viakoo

    Host: Seth Earley, CEO at Earley Information Science

    Published on: September 28, 2026

    In this episode, Seth Earley speaks with John Gallagher, VP of Viakoo Labs at Viakoo, a company that has spent 12 years building automated cyber hygiene for IoT and OT systems across millions of devices. They explore why the physical world - cameras, building automation, water infrastructure, manufacturing equipment - is now the most underprotected attack surface in most organizations, how AI has eliminated the obscurity that passively protected these systems for decades, why ransomware has shifted from stealing data to shutting down operations, why human-in-the-loop is a hard line that can never be crossed in OT remediation, and what it actually takes to build a digital twin of every device in an enterprise environment and use it to match the speed of AI-driven threats.

    Key Takeaways:

    • IT security investments do not transfer to OT and IoT environments - the 150,000 operating systems, device types, and tightly coupled application relationships require a completely separate approach.
    • AI has eliminated security through obscurity - threat actors who previously could not justify the effort to attack niche OT systems can now use AI to read manuals, understand device architectures, and find vulnerabilities at scale.
    • Ransomware has shifted from stealing data to shutting down operations - holding a manufacturing line or energy facility hostage is a fundamentally different and more consequential threat than data exfiltration.
    • Organizations typically have 5 to 20 times more OT and IoT devices than IT systems - the attack surface is orders of magnitude larger than most executives realize.
    • Threat detection in OT is now a solved problem - the unsolved problem is remediation at scale, which requires AI-assisted preparation and autonomous execution with a human in the loop for every deployment decision.
    • A digital twin of every device - tracking make, model, firmware, memory state, configuration, and change over time - is the foundational knowledge layer before any security action can be taken.
    • The defense is not a smarter model - it is knowing what you own, what connects to what, what breaks when you touch it, and who is accountable. That is an inventory problem, a normalization problem, and an information architecture problem.

    Insightful Quotes:

    "AI has brought what we call the inversion. It's taken things like remediation - firmware, password, certificate updates - and said, if you were okay updating even a few hundred devices manually a few times a year, those days are gone. It's a daily occurrence now, and you have to match AI speed." - John Gallagher

    "Will we ever put AI in charge of deploying that firmware update? Never. That is a hard line. There is a strong argument that AI never should be put in a decision-making process in this environment without a human in the loop." - John Gallagher

    "For decades, devices running on the physical side of business were protected by the fact that they were too obscure to be worth an attacker's time. That protection was never a strategy, and AI has erased it. The defense is not a smarter model - it is the knowledge of what you own, the firmware, what connects to it, what breaks when you touch it, who is accountable." - Seth Earley

    Tune in to discover why IoT and OT security is the most consequential and most underestimated cybersecurity challenge in the enterprise today - and what the path from awareness to remediation at scale requires.

    Links

    LinkedIn: https://www.linkedin.com/in/b2bpipelinebuilder/

    Website: https://www.viakoo.com/company/

    Thanks to our sponsors:

    • VKTR
    • Earley Information Science
    • AI Powered Enterprise Book
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    47 min
  • Earley AI Podcast - Episode 100: Running a Business on AI, the Three Loop Framework, and Why Organizations Need to Think Bigger with Bryan McAnulty
    Sep 24 2026
    Why the Organizations Getting the Most from AI Are the Ones That Stopped Treating It as a Tool and Started Treating It as a Collaborative PartnerGuest: Bryan McAnulty, Founder and Product Director at Heights Platform and LatchLoopHost: Seth Earley, CEO at Earley Information SciencePublished on: September 22, 2026In this episode, Seth Earley speaks with Bryan McAnulty, Founder and Product Director at Heights Platform - a platform that has helped over 10,000 creators build online knowledge businesses - and LatchLoop, an AI agent platform he built to run his own company and is now launching for other teams. They explore why most organizations are dramatically underestimating what AI can do right now, how the gap between idea and execution has collapsed to near zero, why unambiguous outcomes are the difference between an agent that delivers and one that invents its own problems, and what a three-loop framework for automation, goals, and feedback changes about how teams work. Bryan shares candid and specific insights from years of running AI-first operations - including what happens when you give agents too much autonomy and the cognitive load lessons that changed how LatchLoop was designed.Key Takeaways:Most organizations are treating AI as a better search engine - the ones that will win are the ones treating it as a collaborative partner capable of long-running autonomous work.The gap between idea and execution has collapsed to near zero - what previously took months of engineering can now be handed off to a model with a well-defined plan and verified in hours.Three loops structure how AI agents should work: automation loops for recurring well-defined tasks, goal loops for longer autonomous work with verifiable outcomes, and feedback loops for iterative back-and-forth work.Unambiguous outcomes are the most important input to any agent - without them, models will invent tasks, solve problems that do not exist, and add unrequested changes that seemed aligned with the goal.Agent guardrails should be structural, not aspirational - not please do not break production but forcing the agent to operate only in the branch, environment, or scope it is authorized to touch.Agent memory and institutional knowledge should be portable - if it lives only inside a vendor's platform, you are building organizational intelligence you cannot take with you.Your ideas are better than the AI's ideas - the implementation belongs to the agent, but the vision, the why, and the how-it-actually-feels-to-a-human belongs to you and always will.Insightful Quotes:"The companies who are gonna win realize that there's a fundamentally different and better thing we can now offer that we could have never done before. And part of the challenge is we're all looking at the same little chat text input that we had in 2023, but the capabilities of the models and the tools behind them are just so much different now." - Bryan McAnulty"You can't say make me the best website. Because make me the best website will give you the most average website. You need to define what best means to you. And if you don't know how to define that to the model, then ask it - what could we do that could make this verifiably true for what I'm looking for?" - Bryan McAnulty"We have a requirements gap now. Because the tools can build these outputs and perform these tasks, it's really about being crisp and precise about what those inputs should be - defining requirements in as much granularity as possible. That is where the human has to show up." - Seth EarleyTune in to discover why running a business on AI requires a fundamentally different way of thinking about work - and what the organizations getting it right have built that most teams have not.LinkedIn: https://www.linkedin.com/in/bryanmcanulty/Heights Platform: https://www.heightsplatform.comLatchLoop: https://www.latchloop.com Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-homedLogos: https://dlogos.xyz/podcasts/earley-ai-podcast-271271ceApple Podcast: https://podcasts.apple.com/podcast/id1586654770Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbEiHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/Stitcher: https://www.stitcher.com/show/earley-ai-podcastAmazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcastBuzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors:VKTREarley Information ScienceAI Powered Enterprise Book
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    36 min
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