--- title: The AI Adoption Journey for Fraud & Risk Teams source_page: https://www.sardine.ai/media/the-saturday-fraud-strategist/episodes/ai-adoption-for-fraud-and-risk-teams canonical: https://www.sardine.ai/media/the-saturday-fraud-strategist/episodes/ai-adoption-for-fraud-and-risk-teams format: text/markdown date: 2026-09-14T04:01:00.000Z description: AI adoption for fraud and risk teams isn’t one leap, it’s five stages. Breaking down AI activation vs AI enablement, and what actually works… --- **Quick links:** [Human page](https://www.sardine.ai/media/the-saturday-fraud-strategist/episodes/ai-adoption-for-fraud-and-risk-teams) · [Home](https://www.sardine.ai) · [Customers](https://www.sardine.ai/customers) · [Blog](https://www.sardine.ai/blog) · [Demo](https://www.sardine.ai/demo) --- # The AI Adoption Journey for Fraud & Risk Teams **Published:** 2026-09-14T04:01:00.000Z AI adoption for fraud and risk teams isn’t one leap, it’s five stages. Breaking down AI activation vs AI enablement, and what actually works… If you’ve been following fraud on LinkedIn for any real stretch of time, you are probably familiar with Brian Davis and have been reading his posts. He has been the first fraud hire at many companies across physical goods, e-commerce, marketplaces, and fintech. Today he sits at the center of it all running deep dive retreats through Safeguard. I have talked with Brian before about AI adoption for fraud and risk teams, and he said something that stuck with me. There’s a real difference between AI activation and AI enablement. Most organizations think they’ve done the second when really they’ve only done the first. I wanted to bring our conversation to all of you, because I think fraud teams may underestimate or overestimate where they sit on this journey. What you’ll hear in this episode: Why AI activation vs AI enablement is the distinction most companies get wrong, and what it actually looks like when you throw a tool over the fence with no guidance. Brian's four pillars for real AI enablement are clear policies, actual training, dedicated incentives and time, and a feedback loop that doesn't die after three weeks. Why change management for fraud teams is really a people management problem wearing a technology costume. Brian's full five-stage framework, covering AI blocked, AI aware, AI enabled, AI first, and AI native, and how to honestly assess where your own team sits. Why AI enablement leadership buy-in has to start at the top, and how executives showing their own AI usage removes the imposter syndrome holding everyone else back. Why so many fraud teams try to go big on day one, transaction monitoring, KYC, and end up frustrated, when the smarter path is workflow design for AI adoption that starts small. Concrete, non-technical AI use cases for fraud, including pattern analysis, internal reporting, and OKR alignment with sales and marketing. How reducing engineering dependency with AI is changing what fraud analyst upskilling with AI actually looks like day to day. Brian's personal framework for fraud practitioner AI use cases, including his own daily habits and how he thinks about build versus buy AI fraud tools. You should listen to this episode if you: Are a fraud or risk leader trying to figure out whether your team is actually AI enabled or just AI activated Are responsible for fraud team AI training or building out fraud team AI governance policies from scratch Are a fraud analyst wondering how to build AI literacy without waiting for your company to hand you a roadmap Are trying to motivate a team through fraud team change management without losing the people who are cautious about the change Are comparing AI first fraud organizations against the fully rebuilt AI native fraud teams and wondering which one is actually the realistic goal ### Episode notes & key takeaways AI activation is not AI enablement, and that gap is where most teams get stuck Brian's framing here really landed for me. AI activation means buying the licenses, rolling out the tool, and giving your team zero guidance beyond "go use it." AI enablement is everything that has to happen after that. It means clear policies on what you can connect to, real training on the dos and don'ts, dedicated incentivized time to actually practice, and a feedback loop that makes sure this isn't just a three-week burst of excitement that fizzles out. Without all four of those pieces together, you get exactly what Brian described. A handful of power users emerge, a much larger group stays cautious and barely uses the tool, and a third group sees no reason to change what already works for them. Leadership has to go first, or nobody else will I loved Brian's point about psychological safety here. When executives visibly use AI themselves, imperfectly and learning in public, it gives everyone else permission to do the same without fear of looking foolish. Without that example, you end up with the worst version of top-down AI mandates, where leadership demands the team become "AI native" while having no real idea what that requires operationally. The five stages run from AI blocked all the way to AI native Brian's five-stage model is the backbone of this whole conversation, and I think it's genuinely useful as a self-assessment tool. AI blocked means you can't use AI yet, for any number of reasons, whether that's missing data, missing tooling, or unclear policy. AI aware means you've dabbled inconsistently, maybe tried it once, without ever really coming back to it. AI enabled means you're using AI for a specific use case, consistently, on a recurring basis. AI first means AI has become core to your decision-making and team structure across multiple use cases. AI native means the entire function has been rebuilt around AI from the ground up, which realistically only applies to companies without much legacy infrastructure to begin with. Most fraud teams right now sit somewhere between AI aware and AI enabled, whether they realize it or not. Start small, and resist the urge to go straight for your biggest, riskiest use case This is the part I really want fraud leaders to sit with. The instinct when you get excited about AI is to go straight for transaction monitoring or KYC, your highest-stakes, most customer-facing processes. Brian's advice runs the opposite direction. He recommends starting in lower-stakes places first, mapping your existing workflows and running pattern analysis and building internal reports. Let your team build real AI literacy and confidence before you ever put it in front of a customer. AI is changing fraud team economics, not just fraud team output Brian said something here that I hadn't quite articulated to myself before. AI is reducing fraud and risk teams' historical dependency on other departments, especially engineering, to get anything built. That's a genuine motivation lever, since fraud teams have always had a lot of ideas and very little budget or headcount to execute them. Reducing that dependency on engineering means fraud practitioners can prototype, test, and even ship internal tools without waiting in someone else's roadmap queue. The echo chamber is lying to you about how far behind you are Brian's closing point might be the one I keep coming back to. If you're on LinkedIn feeling like everyone else is light-years ahead of you on AI, that's an echo chamber talking, not reality. If you're actually spending time learning and experimenting, you're already ahead of the vast majority of the market. That reassurance matters, because FOMO and imposter syndrome are two of the biggest silent blockers standing in the way of a fraud team actually progressing through these adoption stages. ### Final takeaway If there's one thing I want you to walk away with, it's that AI adoption for fraud and risk teams isn't a switch you flip. It's a journey with real stages, and buying a license doesn't put you at the finish line. It puts you at the starting line. The teams that actually get value out of this aren't the ones that moved the fastest, they're the ones that built policies, training, incentives, and feedback loops in alongside the technology. Wherever you honestly sit on that five-stage journey today, the goal isn't to compare yourself to some imagined version of the market that's already ten steps ahead. It's to take the next real step, and then the one after that. Resources & links Not ready to stop the conversation about my, and hopefully your, favorite subject? Subscribe to The Saturday Fraud Strategist newsletter. Connect with Brian Davis | LinkedIn VP at Safeguard Founder, The House of Fraud Advisory Board Member, Association of Certified Fraud Examiners Connect with Chen Zamir | LinkedIn Host of The Saturday Fraud Strategist Helping fintechs build smarter fraud defenses Co-author of “The Fraud Fighter’s AI Playbook”