Celonis Chief Scientist Says Enterprise AI Needs Operational Context to Move Beyond Pilots

Shah, who the episode said has taught AI at MIT as a professor for more than two decades, described that context as central to what he calls “decision intelligence.” AI agents can support individual tasks within larger decision-making processes, but they need to understand the role each task plays and the business conditions surrounding it, he said. “You can’t just do that in a vacuum,” Shah said.

Without the right operational context, agents risk overlooking important constraints, making costly mistakes, or consuming excessive computing resources as they try to work out what they need to know, according to Shah. He said the solution begins with connecting AI to the processes and data enterprises already use.

A contextual layer can help agents understand workflows, operate within defined guardrails, and produce recommendations that people can review and approve. Shah advises organizations to start with a specific business decision, identify its most difficult steps, and test whether AI can improve them. Measuring gains in speed and value can then help determine whether an application is worth scaling.

This approach could also change how employees spend their time. Automating repetitive, manual work and coordinating tasks across teams could free people to focus on more complex strategic decisions. Realizing that benefit, however, will require investment in workforce education, so employees can understand AI outputs and their implications instead of just handing decisions over to agents.

Looking to the future, Shah sees opportunities extending from routine operational tasks to enterprise-wide planning in areas such as finance, workforce management, marketing, and sales. With the right context, AI could help organizations evaluate options and make consequential decisions more quickly. “Now, maybe [resource planning] should not take that much time, and people are actually making the right choices quickly,” Shah said.

The episode was produced in partnership with Celonis.