Most CS teams have bought AI tools. Far fewer have changed their organization to get value from them. These roundtables move past the tooling and look at the foundations underneath it: the data your AI can see, the people who run it, and measuring success. Choose one of three peer-led tables, each hosted by a senior CS leader, and swap notes with peers on what they’ve built, what broke, and what they would do differently. Table 1: One View of the Customer: Building the Signal Layer Your AI Depends On Hosted by Chris Vu, VP of CS, DNV AI can only predict churn or spot expansion if it sees the whole customer. This table covers how leaders pull together product usage, support, commercial and relationship data into one view. It also covers who owns that data and which signals actually predict outcomes. Table 2: The New CS Team: Roles and Skills for an AI-Assisted Org As AI takes on more of the routine work, the CSM role is changing and new roles are appearing. This table looks at how leaders are redesigning team structure, which skills they now hire and train for, and how they explain the change to their teams. Table 3: Proving AI ROI: What to Measure When the CFO Asks AI budgets are now being questioned, and CS leaders are expected to show a return. This table covers which metrics hold up in front of finance, such as capacity freed, coverage per CSM and retention lift. It also covers how to set a baseline before rollout and how to report results without overclaiming.