From AI Pilot Purgatory To Real ROI With Bill Briggs Of Deloitte
Release Date: 02/16/2026
From AI Pilot Purgatory To Real ROI With Bill Briggs Of Deloitte
Tech Talks Daily
In this episode, I’m joined by Bill Briggs, CTO at Deloitte, for a straight-talking conversation about why so many organizations get stuck in what he calls “pilot purgatory,” and what it takes to move from impressive demos to measurable outcomes. Bill has spent nearly three decades helping leaders translate the “what” of new technology into the “so what,” and the “now what,” and he brings that lens to everything from GenAI to agentic systems, core modernization, and the messy reality of technical debt. We start with a moment of real-world context, Bill calling in from San...
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Tech Talks Daily
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Tech Talks Daily
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Tech Talks Daily
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Tech Talks Daily
As someone who spends a lot of time covering AI announcements, product launches, and conference stages, it is easy to forget that most AI today is still built for desks, screens, and digital workflows. Yet the reality is that the vast majority of the global workforce operates in the physical world, on roads, construction sites, depots, and job sites where mistakes are measured in injuries, collisions, and lives lost. That gap between where AI innovation happens and where real risk exists is exactly why I wanted to sit down with Amish Babu, CTO at Motive. In this episode, I speak with Amish...
info_outlineIn this episode, I’m joined by Bill Briggs, CTO at Deloitte, for a straight-talking conversation about why so many organizations get stuck in what he calls “pilot purgatory,” and what it takes to move from impressive demos to measurable outcomes.
Bill has spent nearly three decades helping leaders translate the “what” of new technology into the “so what,” and the “now what,” and he brings that lens to everything from GenAI to agentic systems, core modernization, and the messy reality of technical debt.
We start with a moment of real-world context, Bill calling in from San Francisco with Super Bowl week chaos nearby, and the funny way Waymo selfies quickly turn into “oh, another Waymo” once the novelty fades. That same pattern shows up in enterprise tech, where shiny tools can grab attention fast, while the harder work, data foundations, APIs, governance, and process redesign, gets pushed to the side.
Bill breaks down why layering AI on top of old workflows can backfire, including the idea that you can “weaponize inefficiency” and end up paying for it twice, once in complexity and again in compute costs. From there, we get into his “innovation flywheel” view, where progress depends on getting AI into the hands of everyday teams, building trust beyond the C-suite, and embedding guardrails into engineering pipelines so safety and discipline do not rely on wishful thinking.
We also dig into technical debt with a framing I suspect will stick with a lot of listeners. Bill explains three types, malfeasance, misfeasance, and non-feasance, and why most debt comes from understandable trade-offs, not bad intent. It leads into a practical discussion on how to prioritize modernization without falling for simplistic “cloud good, mainframe bad” narratives.
We finish with a myth-busting riff on infrastructure choices, a quick look at what he sees coming next in physical AI and robotics, and a human ending that somehow lands on Beach Boys songs and pinball machines, because tech leadership is still leadership, and leaders are still people.
So after hearing Bill’s take, where do you think your organization is right now, measurable outcomes, success theater, or somewhere in between, and what would you change first, and please share your thoughts?