Harvard Business Review LogoJuly 1, 2026Illustration by Oscar DuarteThere’s a consistent pattern in failed or underperforming AI initiatives. Business leaders tend to frame AI through the lens of what they see as the most urgent problems—bottlenecks inDespite huge investments on AI deployments, companies have seen returns remain stubbornly modest. Last summer, an MIT report found that 95% of gen AI projects fail. A recent comprehensive large-scale survey conducted by the National Bureau of Economic Research among more than 6,000 senior executives in the United States, United Kingdom, Germany, and Australia found that roughly 90% reported no measurable improvement in productivity attributable to AI cross the last three years. The problem, however, is not that AI does not work. The problem is how leaders think about it.
When Developing an AI Strategy, Beware the Urgency Trap
There’s a consistent pattern in failed or underperforming AI initiatives. Business leaders tend to frame AI through the lens of what they see as the most urgent problems—bottlenecks in productivity, rising costs, slow decision-making, or inefficiencies in workflows. This focus on urgent and immediate challenges may be why AI initiatives start fast and generate excitement, but ultimately fail to transform organizations in meaningful or lasting ways. To avoid this “urgency trap,” leaders can take three actions to avoid employing AI as a quick fix and instead use it as a tool for long-term value creation: 1) prioritize clarity of purpose, 2) resist the urgency bias, and 3) focus on advancing the company’s vision.
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