Summary
Jessica Reeves and Giacomo Korbo discussed why mission-critical customers hesitate to deploy AI: liability, certification, sensitive data, and legacy systems. They argued adoption depends on auditability, hard reliability benchmarks, human expert validation, and incremental modernization rather than wholesale replacement.
Key Topics
5 key topics from Jessica Reeves, Jacomo Corbo and Ron Miller at HumanX Amsterdam 2026. Thicker branches were mentioned more often in the talk.
The Deterministic Engine
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Key Takeaways
- Build audit trails before scaling AI in regulated environments.
- Select lower-certification use cases before automating critical workflows.
- Keep human experts involved for validation and judgment.
- Modernize legacy systems incrementally using decision mapping.
- Demand reliability benchmarks and SLAs before production deployment.
“I think technical debt now is at the boardroom level because it is something that gets in the way of AI adoption”
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