To find out the extent to which organizational information efficiency has improved as generative AI and different AI advances have taken maintain, MIT Expertise Evaluation Insights surveyed 800 senior information and know-how executives. We additionally performed in-depth interviews with 15 know-how and enterprise leaders.
Key findings from the report embrace the next:
• Few information groups are conserving tempo with AI. Organizations are doing no higher as we speak at delivering on information technique than in pre-generative AI days. Amongst these surveyed in 2025, 12% are self-assessed information “excessive achievers” in contrast with 13% in 2021. Shortages of expert expertise stay a constraint, however groups additionally wrestle with accessing contemporary information, tracing lineage, and coping with safety complexity—vital necessities for AI success.
• Partly in consequence, AI is just not absolutely firing but. There are even fewer “excessive achievers” in the case of AI. Simply 2% of respondents price their organizations’ AI efficiency extremely as we speak when it comes to delivering measurable enterprise outcomes. In actual fact, most are nonetheless struggling to scale generative AI. Whereas two thirds have deployed it, solely 7% have completed so extensively.
This content material was produced by Insights, the customized content material arm of MIT Expertise Evaluation. It was not written by MIT Expertise Evaluation’s editorial workers. It was researched, designed, and written by human writers, editors, analysts, and illustrators. AI instruments that will have been used have been restricted to secondary manufacturing processes that handed thorough human evaluate.
