Summary
Ambika Rajagopal explained Michelin’s two-pronged AI approach: broad GenAI access for 30,000+ users, plus custom models that have delivered 200–220 million in ROI over three years. Darko Matovsky argued digital workers go beyond copilots by reimagining entire processes, with leadership—not more tools—the missing ingredient for scaling.
Key Topics
5 key topics from Ambica Rajagopal, Darko Matovski and Akansha Dimri at HumanX Amsterdam 2026. Thicker branches were mentioned more often in the talk.
Digital Workers: What It Takes to Scale Enterprise AI
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Key Takeaways
- Separate productivity copilots from process-level AI that changes how work gets done.
- Build secure internal GenAI platforms before expanding employee access.
- Prioritize custom models for high-ROI business processes.
- Partner with technically deep AI teams to capture latent organizational knowledge.
- Secure leadership mandates before attempting enterprise-wide process reimagination.
“The remaining 80% of the value, from AI to an organization actually comes from building custom models”
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