Celonis Chief Scientist on Context-Aware Enterprise AI
Understand the story
On October 22, 2026, MIT Technology Review published an article presenting the views of Devavrat Shah, Chief Scientist of Enterprise AI at Celonis. He proposed the concept of "decision intelligence," arguing that for AI agents to support specific tasks in enterprise decision-making, they must understand business processes and operational context; otherwise, they may overlook key constraints, make mistakes, or waste compute. As for the path to adoption, he suggested that enterprises first select a specific business decision, identify its most difficult step and test whether AI can improve it, then decide whether to scale up the application by measuring speed and value. He also envisioned AI extending from daily operations in the future to enterprise-wide planning in areas such as finance, human resources, marketing, and sales. Currently this event is covered by a single report, with no further developments.
AI overview of reporting · Updated 2 h前
Reporting timeline
Explore different aspects of the story through its reporting.
- MIT Technology Review · AIMaking the case for context-aware AI
Celonis chief scientist for enterprise AI Devavrat Shah promotes the idea of 'decision intelligence': for AI agents to support specific tasks in business decisions, they must understand business processes and operational context, or they may overlook key constraints, make mistakes, or waste compute. He advises companies to first pick a specific business decision, identify its hardest step, and test whether AI can improve it, then decide whether to scale up by measuring speed and value. He envisions AI eventually extending from daily operations to enterprise-wide planning in finance, HR, marketing, and sales.
Story heat trend
Not enough continuous observations to show a trend yet.