Why AI Agents Need RevOps

Your AI agent says revenue is on track. Your CRO is about to find out you're missing the number by 21%.

Sound familiar?

In this episode, Guillaume Jacquet (CEO & Co-Founder of Vasco) joins Matt Volm to break down why AI agents fail on revenue data, and why the fix belongs to RevOps. The problem isn't hallucination. It's grounding. And there's a four-part framework to solve it.

Guillaume walks through real examples of AI-generated reports that looked great but were built on broken data foundations, the four requirements that move AI accuracy from ~11-30% to ~98%, and why operators should think of agents as hires; not tools.

🎙️ Speakers:

- Guillaume Jacquet, CEO & Co-Founder at Vasco — https://www.linkedin.com/in/jacquet-guillaume/

- Matthew Volm, CEO & Co-Founder at RevOps Co-op — https://www.linkedin.com/in/matthewvolm/

🔗 Resources:

- Vasco (revenue data layer for AI agents): https://www.getvasco.com

- RevOps Co-op podcast library: https://www.revopscoop.com/podcast

- Episode 50: Thinking of AI? Think Data First: https://revopscoop.com/podcast/ai-revops-data-strategy

- Episode 75: How To Go From AI Experiments to Revenue Machines: https://revopscoop.com/podcast/ai-experiments-revenue-machines

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