The loudest AI often isn’t the smartest. We dig into fresh research with Curtis Schroeder, Head of Research and Insight at Varicent, to unpack a striking pattern among 150 revenue leaders: most expect the biggest ROI from system-level AI—forecasting, territory design, quota setting, incentive modeling—while investments still chase seller-facing tools that look great in a demo but struggle to compound impact.
Curtis explains why AI for revenue is really two markets. Seller AI promises instant productivity stories yet demands training, process change, and continuous behavior shifts. System AI upgrades decision quality at the core, creating compounding gains across the org—better coverage, cleaner attainment, faster re-planning, and more credible forecasts. We explore how to separate hype from value, why human skepticism remains the top blocker, and why adoption improves when AI becomes invisible inside workflows rather than another tool reps must learn.
You’ll hear how leaders pair quick visible wins with deeper system investments, how to make forecasting an always-on signal rather than a month-end ritual, and how to link territory potential to quota for fairer, higher-yield plans. We also get real about ROI proof: attribution is messy, but speed, decision quality, and resilience to market shocks are measurable and persuasive. If you’re navigating mandates to “do AI” while chasing durable growth efficiency, this conversation offers a practical blueprint to build trust, compress planning cycles, and invest where results compound.
If the episode sparks ideas, follow the show, share it with a teammate, and leave a quick review—what’s one system-level decision you’d upgrade with AI next?

Download the report mentioned in this podcast:

https://www.varicent.com/info/ai-roi-sales-revops