Pure Signal

Plenty of AI proofs of concept work. Far fewer ever reach scale. On this episode of Pure Signal, hosts Kevin Erickson, Jake Carter, and Ryan Medellin sit down with Mackenzie Knapp, Managing Director, AI Products & Agentic Systems at Credera, to talk about what’s really holding AI back.They cover why AI needs the right foundation to scale, how to map the way your company actually runs, and how leaders can stay close to the work as AI changes it. You’ll also hear why Mackenzie believes fixing the system matters more than replacing the people in it.For leaders wondering where to start, the first step is simple: write down how your company works today, and the bottlenecks will show you what to fix first.—Quotes“It’s not about people being bad. I think people are inherently good. I think systems are designed to continue that behavior.” - Mackenzie Knapp“Too many times people forget about the purpose of the work they’re doing, and they get distracted by the output.” - Mackenzie Knapp“Everyone thought you had to have everything perfectly documented, but the moment you sit down and document, things change.” - Mackenzie Knapp—Timestamps(00:00) Intro(02:52) Why strong AI pilots stall before scale(04:10) Defining the AI operating system(07:53) Mapping how your company really works(14:29) Getting the C-suite hands-on with AI(24:28) Fixing systems, not people(32:02) Purpose over output(41:00) Where to start first(43:33) Closing thoughts—Links Connect with the hosts and guests on LinkedIn!Kevin EricksonJake CarterRyan MedellinMackenzie KnappLearn more about Credera

Every AI pitch looks great on the showroom floor. The hard part comes when someone asks what it costs. On this episode of Pure Signal, hosts Kevin Erickson, Jake Carter, and Ryan Medellin sit down with Dennis Schumacher, Chief Financial Officer in the Professional Services and Technology industries, to talk about how AI actually shows up in the budget.They cover why hours saved isn't the real ROI metric, how to turn AI savings into dollars for experimentation, and whether AI spend belongs in investment or operating expense. You'll also hear Dennis explain why the CFO may matter now more than ever.For executives planning budgets with AI in them, the real test is simple: your costs should level off while your results keep growing.—Quotes“The goal is always to make sure that your non-billable costs don't grow in a linear fashion with revenue because it becomes unsustainable, right? It should grow in more of a plateaued fashion like SG&A does.” - Dennis Schumacher“Make sure you understand the levers that you have as a leader, and that those levers are consistent with the executive team's strategy.” - Dennis Schumacher“I think AI in and of itself is making us ask questions about where do we house that in a budgetary or forecasting cycle, and then how do we validate it in an operating cycle?”  - Dennis Schumacher—Timestamps(00:00) Intro(04:23) First reactions to AI in the boardroom(08:07) The lag between cost cuts and returns(13:42) Where AI ROI shows up in the P&L(16:48) Turning AI savings into experimentation dollars(24:24) Budgeting for agentic labor(40:39) Shadow IT and the rise of the CFO(50:41) Advice for executives right now(01:01:11) Closing thoughts—Links Connect with the hosts and guests on LinkedIn!Kevin EricksonJake CarterRyan MedellinDennis SchumacherLearn more about Credera

Every week brings another call for AI companies to slow down and add guardrails. Banks and insurers have been living under exactly that kind of scrutiny for decades. On this episode of Pure Signal, hosts Kevin Erickson, Jake Carter, and Ryan Medellin sit down with Gail Stout Perry, a Managing Director at Credera, to talk through what AI adoption actually looks like inside Financial Services and Insurance.They cover why banks keep their data siloed, who actually owns your financial data once a fintech app sits on top of it, and why trust and explainability matter more in AI-driven underwriting than almost anywhere else. You'll also hear them debate whether every business, regulated or not, should be operating with that same discipline.For leaders inside compliance-heavy industries, this episode pushes back on the idea that caution only means moving slower. The real skill is knowing where to start.—Quotes“If you start to apply AI to underwriting, and an underwriter looks at the outcome and doesn't agree, then you don't have the trust, right?” - Gail Stout Perry“ You need to enable the use of AI,  especially in a regulated industry; you've got to go slow to go fast.” - Gail Stout Perry“It always comes back to: is the data any good? The defined processes, and where can you start to implement? And then bringing people along.” - Gail Stout Perry—Timestamps(00:00) Intro(01:13) Why regulated industries are different(03:33) How banking and insurance have transformed(05:07) Who owns your financial data(08:25) Trust in AI-driven underwriting(09:55) The Wells Fargo consent decree(11:35) Why insurance may be more AI-ready(15:45) Should every industry regulate AI?(19:54) Closing thoughts—Links Connect with the hosts and guests on LinkedIn!Kevin EricksonJake CarterRyan MedellinGail Stout PerryLearn more about Credera

NVIDIA doubled its earnings year over year and the stock still slipped, because doubling wasn’t enough. That’s the moment this episode starts from: an AI arms race where four or five companies set the tempo for the entire market, and everybody else has to decide how hard to chase them.On this episode of Pure Signal, hosts Kevin Erickson, Jake Carter, and Ryan Medellin work through what the arms race looks like from the executive seat. They get into market concentration and the volatility that comes with it; the fight over data centers, land, and water; eroding trust as an underrated competitive advantage; and how to tell real innovation from AI washing. Along the way they talk through why every business from a donut shop to the Big Five feels obligated to have an AI strategy, when we finally drop “AI” as a prefix, and the uncomfortable truth that AI isn’t taking anyone’s job but the person using it is.Ryan frames the whole thing as a marathon. Most companies aren’t racing to win or racing not to lose; they’re trying to finish the race in good shape. Kevin and Jake close with the questions actually on their minds: how you grow gray-haired experts when AI obviates the apprenticeship model, how a business signals trust, how personal AI productivity becomes enterprise-scale productivity, and why real efficiency takes more time, not less.—Quotes “Are you racing to win, or are you just racing not to lose?” - Ryan Medellin“If you’re an individual employee working for a company and you’re not using tools that are driving that, you literally can’t have a job. So it’s not so much that AI took your job, someone else took your job.” - Kevin Erickson“One of the first things I learned in consulting a long, long time ago is that you either wow with intellect or you bury with BS. What I think is interesting now is that the amount of BS that can come from AI-driven tools is so much. So then it comes back to, well, how do I understand the intellect in the midst of all the data and the noise?” - Kevin Erickson“In a world where trust is eroding because of AI, trust becomes a competitive differentiator for businesses. So then the question is how do you go grow trust, and how do you signal trust if you’re a business?” - Jake Carter“Everyone’s measured on efficiency, and I think that actually to be efficient, you have to have more time. You have got to pound a lot of miles going relatively slow to be effective in the race.” - Kevin Erickson—Timestamps03:08 The NVIDIA news and the AI arms race04:28 Why Hugging Face was the bigger story04:46 Market concentration and structural risk08:44 Data centers, land, and water11:57 How exposed the market is to AI13:49 Back to fundamentals: customers, employees, advantage14:42 Eroding trust and the Edelman Trust Index15:48 Why every business feels it needs an AI strategy18:59 When do we drop the "AI" label?20:23 AI didn't take your job, someone using AI did23:39 Racing to win vs. racing not to lose29:26 Punch cards, prototypes, and the end of the pitch31:27 Real innovation vs. AI washing33:51 Wow with intellect or bury with BS36:56 Why clients are asking for gray hair41:10 Jake's three: experts, trust, and enterprise-scale productivity42:55 Kevin's three: structural change, learning, and boundaries46:43 Closing thoughts—Links Connect with the hosts and guests on LinkedIn!Kevin EricksonJake CarterRyan MedellinLearn more about Credera

Companies walked into this year with a plan to increase efficiency with AI. Fewer walked in with a plan for what comes after. On this episode of Pure Signal, hosts Ryan Medellin, Kevin Erickson, and Jake Carter look back at the predictions everyone made at the start of the year to see which ones actually came true.They cover the shift from efficiency to growth, why the CFO now has a bigger say in AI decisions, and why people, not technology, still decide whether AI actually works. You'll also hear them talk through what's really driving competitive advantage right now, and who should be on the hook when AI moves faster than expected.For enterprise leaders separating what's real from what's just hype, this episode is a candid gut check from three people who've spent all year listening for the signal.—Quotes "You should be able to back it up with proof. You should be able to be able to understand what you did. You should be able to explain the rationale. Otherwise, it's just luck." - Kevin Erickson"The data is right, but really what we mean by that is data and data readiness. Because you can have all the data in the world, if we can't get it to the systems that we need it to be wired into, it's not that valuable." - Jake Carter"Pilots are out, MVPs are in. I don't want something that we're gonna just throw away. We want something that can grow and sustain." - Ryan Medellin—Timestamps00:00 Intro02:11 Setting up the year in review03:20 The efficiency to growth debate07:29 The CFO's growing role in AI decisions09:05 The maturity curve: efficiency, productivity, growth, innovation15:43 The human element of AI26:21 Is data still the ultimate competitive advantage?29:38 Elasticity in leadership37:07 Who bears the risk as AI speeds up delivery?39:26 Closing thoughts—Links Connect with the hosts and guests on LinkedIn!Kevin EricksonJake CarterRyan MedellinLearn more about Credera