RevOps has spent years watching the work: reporting on pipeline, measuring rep activity, auditing whether people followed the process, or whether it was even the right process. Now AI is starting to do the work itself. It enriches records, routes leads, drafts outreach, and in some cases makes the calls that used to need a human. That changes what RevOps is for.

This session gets into what that shift takes on the ground: treating GTM data architecture as the foundation everything else depends on, building governance for when agents are doing revenue work, and knowing where human judgment still needs to sit.

We'll cover:

•⁠  ⁠Why GTM data architecture is the foundation the rest of your AI stack depends on
•⁠  ⁠⁠How to build governance for a world where agents, not just tools, do revenue work
•⁠  ⁠⁠Where human judgment still needs to stay in the loop
•⁠  ⁠⁠Build vs. buy, and how the RevOps operating model has to change

You'll leave knowing what to learn as your team shifts from managing processes to managing agents.