As AI floods the RevTech landscape, RevOps teams are stuck between two paths: invest in building tailored, in-house AI capabilities or rely on off‑the‑shelf platforms that promise “instant intelligence.” This panel brings together RevOps leaders to unpack the trade-offs - cost, speed, control, and risk - and share real stories of what worked, what didn’t, and what they’d do differently. You’ll learn how to: - Evaluate when it makes sense to build custom AI (e.g., routing, scoring, forecasting) versus standardizing on vendor capabilities - Weigh total cost of ownership: data infrastructure, engineering support, model maintenance, and vendor lock-in - Create a practical decision framework that RevOps can use with product, data, and finance to choose the right AI approach for your revenue engine