To determine how organizational data performance has improved with the rise of generative AI and other AI advances, MIT Technology Review Insights surveyed 800 senior data and technology executives. We also conducted in-depth interviews with 15 technology and business leaders.
Key findings of the report include the following:
• Few data teams are keeping pace with AI. Organizations today are no better at executing a data strategy than they were in the pre-AI days. Among those surveyed in 2025, 12% are “excellent” students based on self-assessment data, compared to 13% in 2021. A shortage of skilled talent remains a limiting factor, but teams are also struggling to access fresh data, trace provenance, and resolve security issues—important requirements for AI success.
• Partly because of this, the AI is not yet fully operational. When it comes to AI, there are even fewer “overachievers.” Only 2% of respondents today rate the performance of AI in their organizations highly in terms of achieving measurable business results. In fact, most of them are still struggling to scale generative AI. Although two-thirds used it, only 7% did so extensively.
This content was created by Insights, the content creation division of MIT Technology Review. It was not written by the editors of MIT Technology Review. It has been researched, developed and written by writers, editors, analysts and illustrators. The AI tools that could be used were limited to secondary manufacturing processes that had undergone extensive human testing.
