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Making the case for context-aware AI

Source: MIT Technology ReviewMIT Technology Review InsightsOctober 22, 2026
Read the full story at MIT Technology Review

The article argues that deploying AI in enterprise settings demands more than powerful models—it requires understanding the specific business processes, constraints, and relationships within an organization. Devavrat Shah, chief scientist of enterprise AI at Celonis, advocates for "decision intelligence" that embeds AI agents within defined workflows and provides operational guardrails. Without this contextual layer, AI systems risk overlooking critical business constraints, making costly errors, or inefficiently allocating resources. The recommended approach begins with identifying a specific business decision, isolating difficult steps, and testing AI improvements while measuring speed and

Key points

  • Enterprise AI needs operational context to function effectively within business processes
  • Devavrat Shah promotes "decision intelligence" approach integrating AI with workflows
  • Organisations should start with specific decisions and test AI improvements incrementally
  • Contextual layers help AI agents work within guardrails and produce reviewable recommendations

Summary and key points written by AI from the headline and a short excerpt, so they can be incomplete or wrong. MIT Technology Review did the reporting; read the original for the full story.

Read the full story at MIT Technology Review

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