The Applied AI Podcast

What does it actually take to make AI work in corporate finance, not in theory, but in practice? In this episode, Talbot West CEO Jacob Andra sits down with Reshma Pillai, a finance and AI transformation leader who made an unlikely journey from accountant to AI professional. Reshma brings a uniquely grounded perspective: she's not a computer scientist, and that's exactly why her insights cut through the hype.Together, Jacob and Reshma break down the four core pillars of finance (transactions, reconciliation and controls, forecasting, and narrative reporting) and explore how different types of AI (generative, agentic, predictive ML) map to each one. The conversation gets real fast: why most AI initiatives fail isn't because the use case is wrong, it's because the infrastructure isn't ready and teams are thinking in monolithic tools instead of outcome-driven workflows.They also dig into the concept of "invisible AI," the idea that AI should become the invisible thread connecting finance processes rather than a shiny tool bolted onto existing workflows, and why that framing changes everything about how you design, govern, and scale AI in a compliance-heavy environment like finance.Topics covered:- Why outcomes-first thinking beats technology-first thinking every time- How to string together heterogeneous AI tools into a value pipeline- The accessibility gap: giving non-technical finance professionals the power to build- Failing fast without wasting eight months and a massive budget- SOX controls, audit compliance, and the "human in the loop" debate- Why some of the best AI solutions come from people with zero CS backgroundIf you're a finance leader, digital transformation practitioner, or anyone navigating AI adoption in regulated industries, this episode is packed with frameworks you can actually use.