Moving past pilots: What enterprise AI actually takes

Enterprise AI doesn’t fail because the models aren’t ready. It stalls when operating models, data foundations, and decision paths can’t keep up. Recorded at NRF, this AiR Podcast features Yael Kochman in conversation with Rakesh Srinivasan (The Estée Lauder Companies) and Chris Daniels (Toptal) on what it takes to move from scattered experimentation to repeatable, enterprise deployment - across brands, regions, teams, and partner ecosystems. Key takeaways - Why saturation, skepticism, and a fragmented customer journey are forcing beauty brands to rethink how innovation gets delivered - What must change inside the enterprise to scale AI: product-oriented teams, clear intake and sequencing, and strategy-led roadmaps - The real governance challenge: maintaining brand voice and trust as data flows through platforms, vendors, and generative layers - How modular, “build once, scale many” platforms enable faster deployment across brands - When partnering accelerates outcomes - and why building everything internally can slow progress - A concrete example: Jo Malone London’s Scent Finder and what it shows about treating AI as a product, not a pilot Learn more about The Estée Lauder Companies and Toptal