IT Visionaries

Your people aren't tired of change — they're saturated. There's a difference, and it's the difference between an AI rollout that lands and one that bounces off your workforce entirely. Kelle Fontenot is the Chief Digital Officer at KPMG US, where the CIO, the CTO, and the Chief Data Officer all report to her. She owns internal innovation, architecture, platform, engineering, and data across a 40,000-person workforce — and she's spent the last four and a half years steering that organization through cloud, data, and now an AI wave reshaping how every one of her people does their job. In this conversation, Kelle reframes 'change fatigue' as 'change saturation,' reveals that KPMG employees built 25,000 AI agents in the last six months alone, walks through the synthetic-data acquisition powering regulated AI testing at scale, and explains the brand-new Anthropic partnership turning a 140-year-old services firm into a products company.   What you'll learn • Why 'change fatigue' is the wrong diagnosis — and what 'saturation' changes about how you roll out AI • Why KPMG refuses to use AI as a head-count lever — and why that decision is actually accelerating adoption • How 40,000 KPMG employees built 25,000 AI agents in six months — and what that means for who counts as a 'builder' • Why the CIO, CTO, and CDO all report to one person — and what would break if they didn't • How synthetic data lets a regulated firm test AI at scale without the breach risk • What KPMG's Anthropic partnership signals about the future of professional services   Connect Kelle Fontenot on LinkedIn KPMG US IT Visionaries Podcast   Chapters 0:00 AI Change Has Become AI Saturation 1:29 Why “Change Fatigue” Is the Wrong Diagnosis 3:27 Prompting Like It’s November 4:46 Giving People Space to Innovate 6:38 AI Is Not a Headcount Lever 10:07 Building AI in a Regulated Business 11:24 The Risk Container Around AI 14:12 The AI-Augmented Auditor 17:21 The Agent Governance Problem 20:59 Why Digital, Data, and Tech Sit Together 22:59 Building an Inside Startup 30:04 Innovation Has to Happen at the Edge 36:48 The ROI Math for AI Agents 38:50 Why KPMG Bought a Synthetic Data Company 44:09 KPMG’s Anthropic Partnership 51:03 Shipping AI at Scale 52:10 Kelle Fontenot’s Advice for Leaders -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Companies are making the exact same mistake with AI that they made with cloud. FICO's CIO Mike Trkay breaks down why 95% of companies are failing at AI alignment, why "automating a bad process faster" is the #1 trap, and why regulated industries are already abandoning LLMs in favor of focused language models.   Key takeaways: • Only 5% of AI pilots make it to production — and MIT's research backs it up • The lift-and-shift parallel: cloud costs went up for the same reason AI ROI is missing • Why the LLM-to-focused-language-model shift mirrors cloud-native vs lift-and-shift • What "AI native" actually means (and why chatbots aren't it)   Chapters 00:00 The 5% Alignment Problem 01:09 Only 7% Even Measure If Their AI Works 02:15 "You're Just Doing a Bad Process Faster" 06:29 LLM Repatriation and the Rise of Focused Language Models -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Network automation has been "coming soon" for over a decade. So what's actually different this time? John Capobianco, Head of AI & Developer Relations at Itential, built NetClaw — a CCIE-level AI agent that manages network infrastructure through Slack and WhatsApp. It hit 300 GitHub stars in two weeks. It can analyze packet captures, configure routers, run compliance tests, and generate documentation — all through natural language. John spent 15 years as a network engineer before becoming one of the leading voices in network automation. He's published multiple books, created dozens of open-source projects, and just launched the VibeOps community where 600+ network engineers share AI code without judgment. Key takeaways: • Why natural language is the breakthrough that makes network automation finally work (hint: nobody has to learn Python anymore) • The 5 use cases beyond config management that deliver value on day one — all read-only, all low-risk • How to go from human-in-the-loop to fully agentic network operations without triggering panic • Why "shadow AI" is the new shadow IT — and what leadership needs to do about it • The contrarian case that writing configs by hand is now a solved problem   Guest: John Capobianco — Head of AI & Developer Relations, Itential LinkedIn: linkedin.com/in/john-capobianco-644a1515 X/Twitter: @John_Capobianco NetClaw: github.com/automateyournetwork/netclaw VibeOps Forum: Reach John on LinkedIn or X for invite   Chapters 0:00 Why AI Is Different for Network Automation 2:32 Natural Language: The Interface That Changes Everything 3:51 "The Network Should Be Like a Telephone" — Why Engineers Resist Change 6:08 The No-Win Life of a Network Engineer 8:08 OpenClaw: More GitHub Stars Than Linux 10:15 What NetClaw Actually Does (90 Skills, 43 MCPs) 11:37 The RFC Documentation Problem AI Can Solve 13:03 Day One Agent Rules: Start Read-Only 13:58 When Was the Last Time We Hired a Junior? 15:54 How NetClaw Hit 300 Stars in Two Weeks 19:54 Deterministic vs Non-Deterministic: Getting Engineers Over the Hump 23:36 War Stories: Fat Fingers, MTU Issues, and the DNS Nightmare 28:32 Documentation: The AI Use Case Nobody Can Argue With 32:34 Beyond Config Management: 5 AI Use Cases That Matter Now 36:00 The IDS/IPS Analogy: Why AI Agents Succeed Where Signatures Failed 40:02 AI Hallucination Is Overstated — Misalignment Is the Real Problem 41:53 Model Convergence: Why the Stuff Around the Model Matters More 46:00 Shadow AI Is the New Shadow IT 47:59 What Happens When AI Understands Your Business Context 53:59 The Optimistic Case for AI and Humanity 56:05 VibeOps: Building a Safe Space for AI-Curious Engineers 1:00:36 Is Vibe Coding Just Coding Now? 1:01:54 "Don't Write the Configs Anymore" 1:02:43 Closing & Where to Find John -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Your basic search is missing a massive section of the internet. In this IT Visionaries Spotlight, Chris Brandt talks with Sudheesh Nair, Co-Founder and CEO of TinyFish, about the hidden layer of the internet - the data, pricing, and real-world context that never shows up in search results. The future isn’t better search. It’s AI that can operate the web for you - executing multi-step tasks, navigating complexity, and returning answers that actually reflect your situation.   Chapters: 0:00 The Internet You Never See 1:55 From Search to “Operating the Web” 4:30 The Real Value - From Pricing to Taste   -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

An A.I. the model is similar to a boat in that it needs constant maintenance to perform. The reality is  A.I. models need adjusted boundaries and guidelines to remain efficient.  And when you live in a world where everyone is trying to get bigger and faster and have a certain edge, Scott Clark is helping make that possible with his finely-tuned A.I. modeling techniques.“As you're building up these rules and constructs for how that system will even learn itself, there's a lot of parameters that you need to set and tune. There's all these magical numbers that go into these systems. If you don't have a system of record for this, if you're just throwing things against the wall and seeing what sticks, and then only checking the best one, and you don't have a system of what you tried, what the trade-offs were, which parameters were the most important, and how it traded off different metrics it can seem like a very opaque process. At least that hyper parameter optimization and neural architecture search and kind of tuning part of the process can be a little bit more explainable, a little bit more repeatable and a little bit more optimal.”More explainable, and more optimal, but most importantly scaleable and reproducible. On this episode of IT Visionaries, Scott, the CEO and Co-founder of SigOpt, a company that’s on a mission to empower modeling systems to reach their fullest potential, explains the basic steps that go into successful models, how his team tweaks and optimizes those models to build more efficient processes. Plus, Scott touches on the future of algorithmic models — including how they will improve and where they struggle. Enjoy this episode.Main TakeawaysBad Data, Bad!: When you’re building algorithm models you have to not only focus on the data you are putting into those models, but you have to know where that data is coming from and if that data is trustworthy. When you have untrustworthy data — either its coming from an unknown source or is bias in any way — this can lead to models that deliver poor results.Delivering Consistency: While every algorithm needs to be tweaked and tuned at the start, the best way to deliver consistent, scalable algorithmic models is to make sure you are able to define hyper-specific patterns that the algorithm can abide by. When algorithms know what rules they are looking for (such as this person only likes medium sized shirts with stripes) it has a set of hyper-specific boundaries it can operate off of in order to deliver the best results.Where is the Band Conductor?: Algorithms will continue to infiltrate our everyday lives, but the truth is they still need humans to effectively run them, to tune them, and to make sure that the decisions they are making are the right ones. ---IT Visionaries is brought to you by the Salesforce Platform - the #1 cloud platform for digital transformation of every experience. Build connected experiences, empower every employee, and deliver continuous innovation - with the customer at the center of everything you do. Learn more at salesforce.com/platform -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.