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You may have seen the MIT State of AI in Business 2025 report making headlines this past week, including on LinkedIn. The analysis explores enterprise adoption of generative AI, but the headline finding drawing the most attention is that, despite an estimated $35–$40 billion invested, 95% of pilot projects have failed to deliver measurable business impact, with only 5% scaling meaningfully into production. While this figure is striking, it’s worth noting some limitations that have been expressed, such as: 1) the analysis study is based on just over 300 publicly disclosed AI deployments, 52 structured interviews, and 153 senior leader survey responses—a useful but not comprehensive sample. 2) Some also argue that many AI pilots are still in their early stages and may require more time before meaningful results emerge. 3) In addition, how pilots are designed can significantly influence outcomes. In my book chapter “Enabling Strategic Workforce Planning Through Skills, Artificial Intelligence, and Internal Talent Marketplace”—published in Strategic Workforce Planning: Best Practices and Emerging Directions (SIOP Professional Practice Series, March 29, 2024, edited by Marc B. Sokol and Beverly A. Tarulli)—I emphasized the importance of pilot study design, specifically conducting pilots in areas of the business with a clear pain point to solve and strong leadership support. These two criteria often influence whether a pilot eventually demonstrates value and gains traction. Regardless, the MIT report provides several timely insights that can help practitioners critically evaluate the conditions under which AI initiatives succeed—or stall—in the workplace.
