Autonomous RGM and The Future of Agentic AI

Ask an RGM team how they work today, and the answer is usually some version of this: we come up with the scenarios ourselves, then we test them one at a time. Finance builds its version in Excel, Insights reviews it separately, and the two are reconciled by hand every cycle.

Meanwhile, the agentic AI question is coming from across the business. Analytics teams are being stood up around it. Leadership wants to know the plan. The distance between those two realities is what autonomous RGM actually has to close, and it is a more concrete job than the market's version of the story: a system that finds the possibilities worth testing, so the team spends its time deciding rather than assembling.

Ingo Reinhardt, Founder of Buynomics and author of The Pricing Playbook, works through where agentic AI genuinely applies across the RGM levers, which parts of the work it can take over, and which decisions stay with the team by design. He covers what has to be true before any of it holds: the data, the guardrails, and the ability to explain a recommendation you did not build yourself.

Doug Hampshire, Head of Customer Value, closes by outlining where this stands on the platform today.

What you'll take away:

 

Before Buynomics, Ingo was a Senior Director with Simon-Kucher & Partners, a global leader in pricing. He holds a Ph.D. in Management from the University of Cologne and Master's degrees in Management and Mathematics. Ingo was a PostDoc at the University of Oxford and published in the Strategic Management Journal.