Post by RevOps Co-op

Most teams think their AI problem is a tool problem. It's not. It's a data problem. And if you're automating chaos, you're just getting chaos faster. In our latest RevOps Co-Lab, Ernesto V. (CTO, Traction Complete) brought together three operators who are doing the unglamorous work of rebuilding trust in the revenue data layer, before handing control to agents and AI: 🎙️ Ablla Strainer — Sr. Director of Global Revenue Operations at Fivetran (navigating a full merger integration with dbt Labs) 🎙️ Jon-Sun Lu — Sr. Director of Marketing Operations at GitHub (handling 1–2M net new signups per month) 🎙️ Radu Negru — Head of Data at Inchcape Shipping Services (operating under regulatory and customer-facing data requirements) A few things that hit differently from this conversation: → Ablla's take on mergers: start with the customer map. Don't touch territory models or field mapping until you know who your customers are and how they relate in a hierarchy. Everything else follows from that. → Jon-Sun's "paper cut" principle: don't try to automate mission-critical workflows first. Find the 10-minute manual task you do every day, automate that, build confidence, then go bigger. → Radu's warning: AI isn't just a consumer of data. It's a producer of data. One poorly constrained prompt can generate 100,000 records. The errors compound fast. → The unanimous verdict on human-in-the-loop: don't remove the approval step. Especially for anything touching compensation or territory. "Don't take off the training wheels" until the trust is actually earned. Not assumed. The question from the opening poll still sticks: where is your revenue data layer breaking most today? Source of truth conflicts? Duplicates? Governance gaps? AI readiness? For most people in the room, the answer was all of the above. This session is worth your time if you're trying to build a data foundation that AI can actually run on, not just run over. Peep the highlight reel below ⬇️ 📺 Catch the full session + write-up on our site: https://lnkd.in/gQZYVbHm #revops #revenueoperations #datagovernance #aireadiness #gtm

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