Many enterprises are racing to implement AI, lured by promises of competitive advantage and rapid transformation. However, recent research shows that only about 10% of organizations investing heavily in AI achieve significant financial benefits. The greatest pitfall? Over-reliance on large consulting firms that force generic, cookie-cutter AI solutions into unique business environments. Surveys by MIT, Harvard Business Review, Gartner, and Forrester all reveal a pattern: enterprises guided by consultants often face stalled projects, disappointing results, and an inability to scale pilots into company-wide wins.

Why do these initiatives fail? Big consulting partners tend to prioritize reusable frameworks and fast “wins” over real, customized business value. They downplay the hard, messy foundational work—like data hygiene and change management—required for sustainable AI success. The result is wasted investment, superficial projects, loss of internal knowledge, and poor preparation for future innovation or regulation.

To truly achieve value from AI, companies must develop in-house expertise, focus on what’s genuinely needed for their industry and culture, and build strong data and governance foundations. The lesson is clear: AI can transform, but shortcuts and generic strategies nearly always lead to disappointment, wasted resources, and missed opportunities for real innovation.