AI You Can Trust, Audit and Keep with Russell Moore, Co-Founder & CEO of Amotivv | Episode 494

AI is moving from “helpful assistant” to autonomous actor, and payments leaders are about to feel the difference. I sit down with Russell Moore, Co-Founder and CEO of Amotivv, to get concrete about what breaks when generative AI and agentic AI leave the lab and touch regulated data, customer outcomes, and real money movement. We talk through why so many AI initiatives stall after a promising proof of concept: not because the model is useless, but because teams cannot control the context, prove what happened, or satisfy audit and compliance requirements at scale. Russell explains Amotivv’s three-layer view: persistent AI memory you own, a governed workspace for using any model, and a verification layer (including cryptography and append-only records) that produces tamper-resistant, independently verifiable proof of what AI did, which tools it used, and what policies allowed it. We also dig into practical realities that every fintech team runs into fast: model selection and token costs, why caching and routing matter, and how platform lock-in sneaks in when your vendor effectively owns the memory. On the policy side, we discuss the pace of AI regulation, why the EU AI Act is a useful north star for building “bomb-proof” guardrails, and what it means to be able to prove both usage and non-usage of AI as expectations tighten. If you’re building AI for fraud, marketing, customer support, underwriting, or agentic commerce, this is a roadmap for making it trustworthy.