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ServiceNow Podcast Program is a collection of podcast shows hosted by various ServiceNow experts and professionals covering different focus areas and a broad variety of topics. Come listen to our experts talk about what's going on at ServiceNow. Join the conversation!

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  • 20 episodes
  • Updated Yesterday

Episodes20

Newest first
  • Yesterday · 20 min

    Teaching a Computer to Speak | Voice AI in the Real World

    Voice AI sounds simple until you try to deploy it at scale — across airports, accents, languages, and thousands of employees at once. In this episode of ServiceNow Insights, host Bobby Brill sits down with Midam Kim, an ML engineer and linguist at ServiceNow, to unpack what it actually takes to build voice AI as an enterprise product. From the out-of-vocabulary problem (why AI still struggles with names) to why turn-taking in conversation is a linguistic skill most people never think about, Midam breaks down the human science behind the technology. In this episode: - Why voice AI is replacing typing as the default way to interact with enterprise systems - The difference between building for employees (B2B) vs. building for their customers (B2B2C) - Why an airport is one of the hardest possible environments for voice AI — and what ServiceNow does about it - The "out-of-vocabulary" problem: why AI still struggles with names, accents, and rare expressions - Why ServiceNow's secret sauce is hiring linguists, not just engineers - The linguistic framework behind every voice interaction: sounds, words, and turn-taking - Why voice AI is like teaching a kid to speak for the first time Chapters 00:00 — Welcome to ServiceNow Insights 00:22 — Meet Midam Kim, ML Engineer & Linguist 00:35 — Why voice is replacing typing 01:48 — What voice AI actually does for employees 03:40 — B2B vs. B2B2C: who's really using this? 05:11 — Desk employee vs. airport traveler: two different problems 06:42 — Building for an ever-changing environment 08:53 — Why airports are the hardest use case 09:54 — Accents, fluency, and the diversity problem 11:20 — "My Name Is. My Name Is. My Name Is." — the OOV problem 12:50 — The coffee shop name story 13:20 — How ServiceNow trains its models 14:59 — The 3 linguistic layers: sounds, words, interaction 16:38 — Midam's turn-taking story from Korea 18:33 — Why voice agents can't be "that person you avoid" 20:16 — "We can make it great" Subscribe for more ServiceNow Insights episodes on AI, voice technology, and enterprise innovation. Related episode: Voice AI Agent Evaluation — how ServiceNow measures whether voice AI meets human expectations. https://youtu.be/x7Ks932T18o For more about voice in AI from Midam Kim - https://youtu.be/3NUf6W_FMWs?is=wGc7BfyhiDp8JlOW #VoiceAI #EnterpriseAI #ServiceNow #ArtificialIntelligence #Linguistics #ConversationalAI #AIProduct #Podcast See omnystudio.com/listener for privacy information.

  • July 22 · 25 min

    ServiceNow Process Intelligence | Don't Automate the Chaos

    Most organizations deploying AI agents can’t answer a basic question: is it actually working? Not whether the agent runs — whether the process actually got better. In Episode 3 of our process mining and process intelligence series, Damian Pascale and Roz Parpia join host Bobby Brill to go deep on what it actually looks like to run process intelligence with AI in the mix — from the AI Visibility Gap, to a four-step framework for finding the right AI use cases, to what “closed loop intelligence” really means once agents are governing agents. This episode’s answer to the recurring question: don’t automate the chaos. Find it, understand it, improve it — then, and only then, streamline it. CHAPTERS 0:00 Introduction — Damian Pascale & Roz Parpia 0:56 “Don’t automate the chaos” — where the phrase comes from 2:25 Process mining vs. process intelligence — what actually changed 4:21 The linchpin: where AI fits across all three layers 5:36 The AI Visibility Gap — what most organizations are missing 6:56 A real example: when agent metrics look great, but quality doesn’t 8:13 The four-step framework: Find, Understand, Improve, Streamline 11:27 Where AI comes into streamlining — sizing the right use cases 13:19 Does the order of the four steps actually matter? 14:04 Task Mining — the human side process mining can’t see 15:19 A concrete example: the procurement approval bottleneck 16:31 The closed loop — six steps to continuous improvement 17:30 Why you can never skip the ‘detect’ step 18:05 Measuring real impact with the compare feature 19:25 Governance and AI Control Tower, explained simply 20:46 Mining the agents themselves — a third layer of visibility 21:36 Closed loop intelligence — the three layers, confirmed 22:48 Day one: what to do after deploying your first agent 23:38 Closing thoughts from both guests 24:26 Wrap-up IN THIS EPISODE • Why an AI agent doesn’t fix a broken process — it just runs the broken process faster • The real difference between process mining and process intelligence: three layers in one • The AI Visibility Gap: why almost every customer has deployed an agent, but few can prove it’s working • A real customer example — an agent that improved response time but quietly increased the reopen rate • The four-step framework for AI-ready process improvement: Find, Understand, Improve, Streamline • The 2–15 minute rule (and the 3–9 minute sweet spot) for sizing the right AI agent use cases • Why skipping straight to automation is exactly how you end up automating the chaos • Task Mining and the procurement approval example — 45 minutes across four systems, invisible to process mining alone • The six steps of the closed loop, and why the ‘detect’ step is the one everyone skips • Using the compare feature to measure whether an AI agent actually helped — or just moved the problem • AI Control Tower, explained simply — and how it becomes a third layer of process intelligence • Closed loop intelligence: the agent, the governance, and the agent’s own behavior — all observable, all improving GET STARTED If you’re a ServiceNow customer, you already have access to free evaluation projects — no license needed. https://www.servicenow.com/au/products/process-mining/get-started.html https://www.servicenow.com/docs/r/now-intelligence/process-mining/process-mining.html https://www.youtube.com/watch?v=TVrU0TQ7ldM https://www.youtube.com/watch?v=GLKROYqnc10 #ServiceNow #ProcessMining #ProcessIntelligence #AIAgents #AgenticAI #TaskMining #AIGovernance #AIControlTower #WorkflowAutomation #DigitalTransformation #ContinuousImprovement #ClosedLoopIntelligence #ServiceNowPodcast #EnterpriseAI #DontAutomateTheChaos See omnystudio.com/listener for privacy information.

  • July 9 · 23 min

    ServiceNow Process Intelligence | From Sticky Notes to Process Maps in Five Minutes

    Is process mining just Six Sigma with better software? Two former Lean Six Sigma consultants — now Product Managers at ServiceNow — answer that question. The answer is more interesting than you’d expect. Tomas Galle (Six Sigma Black Belt) and Roz Parpia (Green Belt) join host Bobby Brill to trace process intelligence from factory floors and sticky-note whiteboards to process maps generated in under ten minutes from data you already own. They cover the real cost of the old way, non-conformance, the ServiceNow Playbooks feature, Task Mining, and the question every AI agent deployment should be asking but usually isn’t: did the process actually get better? CHAPTERS 0:00 Introduction — Tomas Galle & Roz Parpia 2:02 Is process mining just Six Sigma? 4:13 The belt system explained — Black Belt, Green Belt, and the punchline 4:58 Manufacturing observation: what process improvement looked like before 7:51 The real cost of the old way — six figures, six months, one process 8:46 Customer reaction: ten years of work, solved in ten minutes 9:03 Where ServiceNow sits in the Process Intelligence market 10:56 Annual physical vs. wearable — continuous vs. snapshot 13:13 Conformance checking and the happy path 14:10 Non-conformance: what it is and why everyone should care 16:58 Static statistics vs. analysis on the move 17:05 Playbooks: responding to non-conformance in real time 18:54 How to get started today — free evaluation projects, no license needed 20:26 Task Mining: the human layer process mining can’t see 22:00 You’re already sitting on a goldmine 22:53 Closing thoughts IN THIS EPISODE • Why “that’s just Six Sigma” is actually the right reaction — and what it’s still missing • Frederick Taylor’s stopwatch, the Gemba walk, and how the factory floor became the IT service desk • Why a single process improvement engagement used to cost six figures and take up to six months • The Gartner Magic Quadrant for Process Intelligence — and Roz’s candid take on where ServiceNow really stands • The wearable vs. annual physical: why continuous process mining beats the yearly audit • Conformance checking and the happy path — what it means when your process deviates • Non-conformance explained with a real change management example (87% vs. 98% CAB approval) • How the ServiceNow Playbooks feature turns detection into real-time correction with one click • Task Mining: what people do in Outlook, Teams, and Excel that never appears in your process map • How to start mining your own data today — no license required, no IT admin needed GET STARTED If you’re a ServiceNow customer, you already have access to free evaluation projects — no license needed. https://www.servicenow.com/au/products/process-mining/get-started.html https://www.servicenow.com/docs/r/now-intelligence/process-mining/process-mining.html https://www.youtube.com/watch?v=TVrU0TQ7ldM https://www.youtube.com/watch?v=GLKROYqnc10 TAGS #ServiceNow #ProcessMining #ProcessIntelligence #SixSigma #LeanSixSigma #TaskMining #AIAgents #WorkflowAutomation #DigitalTransformation #ContinuousImprovement #NonConformance #Playbooks #ServiceNowPodcast #EnterpriseAI #ProcessImprovement #GembaWalk #ConformanceChecking See omnystudio.com/listener for privacy information.

  • June 17 · 23 min

    The Cost of Building the Right Thing | AI, Speed & Discernment at ServiceNow

    Engineering teams are building ten times — even a hundred times — more than they could two years ago. That's a win, but one not without challenges. Because the cost of building the right thing has climbed exponentially. In this episode of the ServiceNow Insights podcast, host Bobby Brill sits down with three leaders who are living this tension from three distinct angles: the content and design leader who first spotted the productivity math problem, the design VP pushing for discernment over speed, and the research lead keeping the human at the center. ━━━━━━━━━━━━━━━━━━━━━━━━ IN THIS EPISODE ━━━━━━━━━━━━━━━━━━━━━━━━ DAVID HOARE — Group VP, Digital Content & Design, ServiceNow ANAND THARANATHAN — Group VP, Product Research & Insights, ServiceNow DANTLEY DAVIS — SVP of Design, ServiceNow ━━━━━━━━━━━━━━━━━━━━━━━━ CHAPTERS ━━━━━━━━━━━━━━━━━━━━━━━━ 0:00 Introduction & Guest Intros 1:13 David: The AI Philosophy — ChatGPT as genuine inflection point 3:02 David: Economic viability — why AI unlocks what was never possible before 3:12 Anand: Three-person startups scaling to $100M+ 3:45 Dantley: From 3D Studio Max to Jarvis — AI as human superpower 6:29 Anand: The customer north star hasn't changed 7:10 David: Engineering's survival problem — the 100x production gap 8:32 David: Andrew Ng's PM-to-engineer ratio + the cost of building wrong 9:40 Dantley: Nine concepts in an hour — design velocity and discernment 12:04 Dantley: The hip-hop tastemaker — slowing down as part of the process 14:20 David: Content governance — the fox guarding the hen house 16:21 Anand: Trust and the human-AI system 17:20 Dantley: AI surprise — UI tech stacks, feature completeness & hidden tech debt 20:21 18-Month Close — Anand, Dantley & David ━━━━━━━━━━━━━━━━━━━━━━━━ KEY TAKEAWAYS ━━━━━━━━━━━━━━━━━━━━━━━━ • Engineering is the first function to see massive AI productivity gains — but that creates a gap every other function has to survive • The cost of building has dropped. The cost of building the wrong thing has climbed exponentially • Discernment is the bottleneck — not speed. Nine concepts in an hour still needs a tastemaker • AI quality is only as good as the content signals it receives — governance is not optional • The customer north star hasn't changed. AI just changes how fast you can move toward it • Customer value is the only metric that matters. Everything else is the path to it ━━━━━━━━━━━━━━━━━━━━━━━━ ABOUT THIS PODCAST ━━━━━━━━━━━━━━━━━━━━━━━━ Subscribe for new episodes on AI, product, engineering, and the future of work. #ServiceNow #AI #ArtificialIntelligence #ProductDesign #SoftwareEngineering #ContentGovernance #DesignLeadership #AIStrategy #ProductManagement #EngineeringLeadership #TechLeadership #FutureOfWork #ServiceNowInsights #MachineLearning #Innovation #DesignThinking #TechPodcast #AIProductivity #DigitalTransformation #CustomerValue See omnystudio.com/listener for privacy information.

  • May 29 · 34 min

    6th YEAR SEASON FINALE: Juan and Tim Rant

    Can't believe it's already been 6 years. Thank you to our amazing guests and specially our listeners. In this season finale episode, Juan and Tim rant about the honest no-bs discussions they've had in 2026 and what are the topics they are looking forward to cover in the next season. See omnystudio.com/listener for privacy information.

  • May 27 · 24 min

    Being AI Native at ServiceNow

    What does it actually mean to be AI native? Not the buzzword — the real thing. Host Bobby Brill brings together seven ServiceNow experts across six conversations for a complete picture of what AI native thinking, building, and working looks like right now. ━━━━━━━━━━━━━━━━━━━━━━━━ WHAT WE COVER ━━━━━━━━━━━━━━━━━━━━━━━━ DI LE — AI Ethicist & Human-Centered AI Strategist, ServiceNow The clearest definitions you'll find anywhere of responsible AI, ethical AI, and human-centered AI — and why all three are required if you're going to do this right. Plus: why AI native means AI as the operating system, not a feature. DR. ALAINA BEAVER — Global Head of Accessibility Customer Engagement, ServiceNow ServiceNow built the world's first AI model accessibility checker with the Global Accessibility Awareness Day Foundation — and open-sourced it on GitHub for free. Because responsible AI native behavior means holding AI itself accountable. ANAND THARANATHAN — Research Leader, ServiceNow A framework from cognitive science every AI builder needs: use, disuse, misuse, and abuse. The four modes of AI interaction — and why proper use is the only one that delivers. TARA BOGAVELLI & KATRINA STANKIEWICZ — Voice AI Research Team, ServiceNow How ServiceNow built a rigorous open-source evaluation framework for voice agents from scratch — and what cascade failures, transcription errors, and prosody failures actually sound like in practice. IAN THURLOW & ANDREW YAN — Software Engineering Manager & Software Engineer, ServiceNow The daily ground-floor reality of being AI native: AI as accelerator, AI as the new Stack Overflow, the calculator analogy, and why fundamentals matter more than ever. ━━━━━━━━━━━━━━━━━━━━━━ LEARN MORE ━━━━━━━━━━━━━━━━━━━━━━━━ ServiceNow Responsible AI: https://www.servicenow.com/responsible-ai AI Model Accessibility Checker: https://www.servicenow.com/accessibility-statement.html ServiceNow AI: https://www.servicenow.com/artificial-intelligence ━━━━━━━━━━━━━━━━━━━━━━━━ ABOUT THIS PODCAST ━━━━━━━━━━━━━━━━━━━━━━━━ Hosted by Bobby Brill. A ServiceNow podcast exploring the people, technology, and ideas shaping the future of work. #AINative #ServiceNow #ResponsibleAI #HumanCenteredAI #AIEthics #EnterpriseAI #FutureOfWork #NowAssist #ArtificialIntelligence #Podcast See omnystudio.com/listener for privacy information.

  • May 20 · 43 min

    Pragmatic Use-Case-Driven Data Governance with Jason Doerr

    Jason Doerr has spent years watching governance programs undermine themselves by cataloging everything without a use case, naming data stewards who have nothing to actually do, and building central teams that become blockers instead of enablers. In this episode, he walks through what pragmatic governance actually looks like: start with use cases, give stewards real work to action on, and let the central team set principles rather than police behavior. He also digs into PADU (Preferred, Acceptable, Discouraged, Unacceptable) as a practical roadmap framework, how LLMs can accelerate semantic layer creation without generating vanity metrics, and why the governance operating model is shifting toward agentic management ... whether the governance community is ready for it or not. See omnystudio.com/listener for privacy information.

  • May 20 · 5 min

    TAKEAWAY - Pragmatic Use-Case-Driven Data Governance with Jason Doerr

    This is the takeaway episode with Jason Doerr who has spent years watching governance programs undermine themselves. He walks through what pragmatic governance actually looks like and digs into PADU (Preferred, Acceptable, Discouraged, Unacceptable) as a practical roadmap framework. See omnystudio.com/listener for privacy information.

  • May 15 · 48 min

    Data Catalyst³: Governance × Change Management × Data Fluency w/ Bob Seiner

    Bob Seiner has spent decades in data governance, and in this episode he joins Juan and Tim to unpacks his new framework, Data Catalyst Cubed, which multiplies data governance by change management and data fluency. Miss any one of them, and you get zero. The problem is that leadership has never treated behavior change as part of the governance mandate, and most data programs have never connected with the change management expertise that already exists inside their organizations. See omnystudio.com/listener for privacy information.

  • May 13 · 29 min

    Day One Ready: What New Engineers Need to Know About AI — Engineering Now Unlocked

    Day One Ready: What New Engineers Actually Need to Know About AI | Engineering Now Unlocked Starting your first engineering role — or coming back for a return offer — and wondering what AI actually changes about the job? This episode gives you the real answer, from two engineers living it every day. Jordan Shelton and Cynthia Mathenge sit down with Ian Thurlow (Senior Manager, Data Platform Software Engineering) and Andrew Yan (Software Engineer, Data Foundations) to talk about what day one looks like now, what AI tools actually do for early-career engineers, and what fundamentals still separate good engineers from great ones. If you’re about to start an internship, just got your return offer, or you’re a manager thinking about how to set new engineers up for success — this is the conversation you need before day one. What you’ll learn ✔ What AI actually changes about day-to-day engineering work (and what it doesn’t) ✔ Why the fundamentals matter more than ever — not less ✔ How to build a network at a company like ServiceNow, even if you start remotely ✔ How to use AI as a sounding board, not a crutch Chapters 00:00 Introduction — Engineering Now Unlocked 02:08 Meet Ian Thurlow and Andrew Yan 03:03 How AI is changing day-to-day engineering work 04:47 AI as an accelerator, not a replacement 09:04 AI as a sounding board 12:38 Leadership mindset in an AI-first team 13:46 Raising the bar for early-in-career talent 1 5:41 What your first 30 days should look like 17:43 This or That 19:16 Code reviews: the fastest way to learn that nobody talks about 20:57 Building your network — even fully remote 24:24 Ian and Andrew’s Work Advice 27:43 Outro Guests Ian Thurlow Senior Manager, Data Platform Software Engineering — ServiceNow Andrew Yan Software Engineer, Data Foundations — ServiceNow Hosts Jorden Shelton Technical Program Manager, AI Engineering & Delivery — ServiceNow Cynthia Mathenge Business Operations Manager, AI Engineering & Delivery — ServiceNow Bobby Brill ServiceNow Insights Links & Resources Learn more about ServiceNow Engineering → https://www.servicenow.com/company/careers/engineering.html ServiceNow Docs → https://docs.servicenow.com New to the channel? Subscribe so you never miss an episode of ServiceNow Insights. See omnystudio.com/listener for privacy information.

  • May 7 · 40 min

    AI Governance Isn't Compliance. It's About Humans with Victoria Gamerman

    Most organizations are treating AI governance as a compliance checkbox. Victoria Gamerman argues it's the gateway that finally forces organizations to confront the human side of AI adoption. In this episode, Victoria breaks down why the POC-to-operationalization gap is so hard to close, why people, process, and data each carry more human weight than most leaders acknowledge, and what "AI-ready data" actually means and a reminder that AI isn't a technology problem. It never was. See omnystudio.com/listener for privacy information.

  • May 1 · 53 min

    AI Appetite Is Easy, Digestion Is Hard with Diana Wu David

    Everybody wants AI. AI adoption conversations are dominated by tools, models, and metrics. Far fewer organizations have figured out what to do with it once it's inside the building. The harder question, one that most leaders are avoiding, is what happens to the humans? Diana Wu David, Director of Futures at ServiceNow joins Juan and Tim to unpack what leaders should and should not be doing. See omnystudio.com/listener for privacy information.

  • May 1 · 5 min

    TAKEAWAY - AI Appetite Is Easy, Digestion Is Hard with Diana Wu David

    This is the takeaway episode with Diana Wu David, Director of Futures at ServiceNow where we discuss AI adoption, the metrics and how far fewer organizations have figured out what to do with AI once it's inside the building. See omnystudio.com/listener for privacy information.

  • April 29 · 29 min

    EVA - A Framework for Evaluating Voice Agents by ServiceNow

    Voice AI agent evaluation — why it's fundamentally harder than text, how cascade failures derail conversations invisibly, and ServiceNow's open-source framework to establish industry evaluation standards. Featuring real audio examples showing authentication failures, leaked reasoning, and latency problems. WHAT WE COVER TARA BOGAVELLI — Research Engineer, ServiceNow Leading the open-source voice agent evaluation framework. Explains why existing benchmarks don't measure what matters and what ServiceNow is releasing to establish industry standards. KATRINA STANKIEWICZ — Staff Machine Learning Engineer, ServiceNow Cascade model architecture expert. Breaks down STT → LLM → TTS failure modes, named entity transcription challenges, and real audio example analysis. GABRIELLE GAUTHIER MELANÇON — Staff Applied Research Scientist, ServiceNow Multi-language evaluation specialist. Reveals why Large Audio Language Models lag behind, the native speaker requirement, and bot-to-bot simulation methodology. CHAPTERS 0:00 Introduction — The evaluation gap 1:11 ServiceNow's Open-Source Framework Announcement — Tara Bogavelli 2:43 Meet the Researchers 3:43 Voice-Specific Challenges — Tara Bogavelli 5:03 Cascade Architecture: STT → LLM → TTS — Katrina Stankiewicz 7:57 The Named Entity Problem — Katrina Stankiewicz 10:06 Evaluation Metrics: Accuracy vs Experience — Gabrielle Gauthier Melançon 11:23 Bot-to-Bot Testing at Scale — Gabrielle Gauthier Melançon 14:30 The LALM Gap: Why Audio AI Judges Struggle — Tara Bogavelli 16:57 Real Audio Example: Flight Rebooking Gone Wrong 21:58 Breaking Down the Failures — Katrina Stankiewicz 28:30 Wrap-Up & Resources KEY INSIGHTS The Cascade Failure Problem: STT → LLM → TTS errors propagate invisibly Named Entity Transcription: The #1 enterprise blocker—names, confirmation codes, emails break authentication Accuracy vs Experience: Perfect task completion means nothing if users hang up due to poor experience LALM Gap: Large Audio Language Models lag behind text LLMs—human evaluators remain essential Latency Kills Conversations: Five-second pauses make users think the call dropped, breaking the experience even when tasks complete Open-Source Framework: ServiceNow releasing evaluation tools, metrics, and bot-to-bot simulation methodology for the industry. LEARN MORE Website: https://servicenow.github.io/eva/ GitHub: https://github.com/servicenow/eva Blog Post: https://huggingface.co/blog/ServiceNow-AI/eva Dataset: https://huggingface.co/datasets/ServiceNow-AI/eva ABOUT Hosted by Bobby Brill. ServiceNow Insights podcast explores AI research, real-world applications, and the people building the future of work. #VoiceAI #AIEvaluation #ServiceNow #MachineLearning #OpenSource #ConversationalAI #STT #TTS #LLM #VoiceAgents #AIResearch #Podcast See omnystudio.com/listener for privacy information.

  • April 24 · 38 min

    It's Friday: Juan and Tim rant about AI, Agents, and the Uncomfortable Truth About Data's New Center of Gravity

    Juan and Tim's Friday rant covers a lot of ground, from Juan's TED takeaways on AI's unprecedented speed and what it means for humanity, to the uncomfortable shift data teams need to make: work and decisions are the point, not pipelines and gold layers. They dig into what Medallion Architecture 2.0 looks like (feedback loops, insights to action, agent governance), why organizational design theory applies directly to agent swarms, and what library science can teach us about the future data stack. The thread running through all of it: the humans who thrive in this moment won't be the ones who build the most, but the ones with taste. See omnystudio.com/listener for privacy information.

  • April 16 · 52 min

    Think Like a Librarian: Why the Reference Interview Is the Framework Data Teams Are Missing with Jenna Jordan and Amalia Child

    Data teams spend enormous energy building pipelines, platforms, and governance frameworks but often skip the most fundamental step: truly understanding what people are actually asking for. In this episode, Juan and Tim sit down with data librarians Jenna Jordan and Amalia Child to explore why library science may be the missing lens for data work. At the heart of the conversation is the reference interview, a structured technique librarians use to uncover a user's "true information need," which almost never matches the first question they ask. From establishing trust and listening without judgment, to asking open-ended questions and verifying whether the need was actually met, the reference interview offers a rigorous, repeatable framework for anyone serving data users. If you've ever wondered why data projects deliver less value than expected, this episode will reframe the problem entirely and give you a practical toolkit to start closing the gap. See omnystudio.com/listener for privacy information.

  • April 15 · 6 min

    TAKEAWAY - Think Like a Librarian: Why the Reference Interview Is the Framework Data Teams Are Missing with Jenna Jordan and Amalia Child

    Data teams obsess over pipelines and platforms but often skip the most fundamental step: truly understanding what people are actually asking for. We chat with data librarians Jenna Jordan and Amalia Child who share a framework for exactly that; it's called the reference interview, and it might be the most practical toolkit data teams have never used. See omnystudio.com/listener for privacy information.

  • April 15 · 18 min

    AI Control Tower - Governing AI at Scale with ServiceNow

    AI governance at scale — what it means, how to do it, and what regulations you need to know now. Host Bobby Brill brings together five ServiceNow experts across two conversations for a complete 20-minute briefing on governing AI in the enterprise. ━━━━━━━━━━━━━━━━━━━━━━━━ WHAT WE COVER ━━━━━━━━━━━━━━━━━━━━━━━━ RAVI KRISHNAMURTHY — VP, AI Platform, ServiceNow Why hidden AI is one of the biggest unmanaged risks in the enterprise — and why governance is an accelerator, not a brake. PETER WEIGT — Responsible AI, ServiceNow The innovation paradox: how AI Control Tower makes governance a team sport and breaks down the silos that slow AI deployment down. SAMPADA CHAVAN — AI Control Tower, ServiceNow How AI Control Tower was built, what the discovery problem really looks like, and why compliance must be baked into the AI lifecycle — not bolted on at the end. ANDREA LAFOUNTAIN — AI Legal, ServiceNow The three regulatory frameworks every enterprise needs to know: EU AI Act, Colorado AI Act, and NIST. Plus: the compliance strategy that scales across all of them. NAVDEEP GILL — Responsible AI, ServiceNow The math on enterprise AI compliance — why it's exponential — and how AI Control Tower's automated discovery keeps you ahead of it. ━━━━━━━━━━━━━━━━━━━━━━━━ CHAPTERS ━━━━━━━━━━━━━━━━━━━━━━━━ 0:00 Introduction 1:23 The Hidden AI Problem — Ravi Krishnamurthy & Sampada Chavan 5:33 AI Control Tower in Practice — Peter Weigt & Sampada Chavan 7:37 The Regulatory Landscape — Andrea LaFountain & Navdeep Gill 14:38 Compliance in Action & Key Deadlines 17:05 Wrap-Up ━━━━━━━━━━━━━━━━━━━━━━━━ KEY DATES TO KNOW ━━━━━━━━━━━━━━━━━━━━━━━━ EU AI Act enforcement: August 2026 Colorado AI Act enforcement: June 2026 NIST AI RMF: Voluntary framework, increasingly referenced by regulators ━━━━━━━━━━━━━━━━━━━━━━━━ LEARN MORE ━━━━━━━━━━━━━━━━━━━━━━━━ ServiceNow AI Control Tower: https://www.servicenow.com NIST AI Risk Management Framework: https://www.nist.gov/artificial-intelligence ━━━━━━━━━━━━━━━━━━━━━━━━ ABOUT THIS PODCAST ━━━━━━━━━━━━━━━━━━━━━━━━ Hosted by Bobby Brill. A ServiceNow podcast exploring the people, technology, and ideas shaping the future of work. #AIGovernance #ServiceNow #AIControlTower #ResponsibleAI #EUAIAct #EnterpriseAI #AICompliance #FutureOfWork #NowAssist #Podcast See omnystudio.com/listener for privacy information.