Creating AI value with enterprise context

In most organizations, multiple AI platforms and tools coexist—customer‑service systems, conversational assistants, and process‑automation solutions. Although each of these technologies is advanced and responsive, the outcomes they produce often lack deep business insight, making it hard to realize real benefits. A MIT Technology Review Insights study shows that while all surveyed companies use AI to some extent, only 16 % achieve transformative value. Forty percent see moderate improvements in specific tasks or teams, 21 % report significant gains, and 23 % barely obtain returns.

Many firms remain in pilot phases (38 %) or use AI to support staff through copilots and chat assistants (35 %). Only 12 % have AI agents in production, and just 3 % deploy them for most critical processes. According to Prukalpa Sankar, co‑founder of Atlan, the main gap lies in the absence of a “context layer”—an infrastructure that links enterprise systems to AI models, enabling artificial intelligence to interpret and apply business knowledge in a governed way.

This news is significant because it illustrates that AI’s potential is not realized merely by powerful models; it requires proper integration of business context. Understanding and closing that gap is essential for AI investments to deliver sustainable returns and enhance organizational competitiveness.

Read the original article on MIT Technology Review

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