Why 90% of Executives See No AI Productivity Gains — and How to Break the Pattern

Despite enormous investment in AI, most enterprise deployments are producing disappointing results. A recent MIT report found that 95% of generative AI projects fail. A large-scale survey by the National Bureau of Economic Research of more than 6,000 senior executives across the US, UK, Germany, and Australia found that roughly 90% reported no measurable productivity improvement attributable to AI over the past three years.

David De Cremer — professor of management and technology at Northeastern University and Dean of the D'Amore-McKim School of Business — argues in Harvard Business Review that the failure isn't AI's fault. The problem is how leaders think about it.

The Urgency Trap

Business leaders consistently frame AI through the lens of their most pressing problems — bottlenecks, inefficiencies, competitive pressures demanding immediate action. This "urgency trap" drives organizations to deploy AI reactively, targeting visible pain points rather than building toward strategic capability.

The result is a pattern of initiatives that solve isolated problems but fail to compound into measurable enterprise-wide value. Short-term urgency crowds out the longer-horizon thinking needed for AI to deliver durable returns.

Key Takeaways

• The failure rate of AI initiatives stems from how leaders frame the problem, not AI's capability
• Urgency-driven AI strategy produces fragmented deployments that don't scale
• Sustainable AI adoption requires grounding initiatives in strategic priorities, not operational firefighting

Read the full article on Harvard Business Review