AI is exposing the operational gaps retailers have ignored for years

AI demos are impressive but making AI work reliably (and valuably) across a retail business is another story. In this special compilation episode, Kailin Noivo brings together insights from seven retail and technology experts on what separates experimentation from real results. From production guardrails and problem-first adoption to AI-driven search, internal training and automated website fixes, these conversations reveal how retailers are putting AI to work where it matters.

Most AI tools still stop at the recommendation. Mory Katan is building something different. He explains how WiseBird Systems’ Owl connects business context, customer data, website behavior, and execution, so teams can move from “here’s what you should do” to actually testing, deploying, and learning from the result. At LiLi Tile, Mory is putting that approach into practice across website optimization, CRO, CRM, inventory and warehouse operations.

Managing a conglomerate of apparel brands requires a flexible and nimble approach to operational flexibility. Debra Sabourin from Perry Ellis International explains how her team uses internal systems to scale across different demographics while keeping a lean headcount. She shares the importance of the AI champion initiative and how it helps different departments adopt new tools to analyze complex business data.

There’s a dangerous trap many businesses are falling into - trying to bolster AI onto every process. Chief Product Officer Ramzi Rahbani proposes a different route, he explains why FortNine starts with the customer problem first, then uses AI where it can genuinely improve shopping, service, site optimization, and the ownership experience

Jamie Pinsky didn’t wait for an AI budget, a dedicated team, or a consultant. He started with a few small operational pain points and ended up building dozens of agents that now support reporting, data validation, retailer monitoring, and day-to-day ecommerce operations at Renwil.