Devavrat Shah argues for enterprise AI guided by operational context

In an interview with MIT Technology Review, Devavrat Shah, Celonis’s chief scientist of enterprise AI, says AI agents need to understand operational context—including each task’s role, business constraints, and surrounding conditions—to support enterprise decisions. Without it, he says, systems may overlook important limits, make costly mistakes, or consume excessive computing resources. The Business Lab podcast episode was produced in partnership with Celonis.

Shah recommends connecting AI to the processes and data companies already use, with a contextual layer, guardrails, and human review. He suggests starting with a specific decision, testing its most difficult steps, and measuring gains in speed and value before scaling. According to Shah, automating repetitive tasks could free employees for strategic decisions, but organizations will need to invest in workforce education so people understand AI outputs and their implications.