Here’s The Real Reason 75% of Corporate Gen AI Initiatives Fail

Many AI initiatives fail because companies rely on outdated business models and fail to integrate human intuition with AI-powered systems.

Business leaders are rushing to harness the quasi-magical powers of artificial intelligence (AI), with a projected annual spend of $60 billion on AI models by 2026. Yet, revenue from AI is only expected to reach about $20 billion per year by that point, flagging a substantial gap between investment and returns. In fact, recent studies show that roughly 75% of Gen AI initiatives don’t succeed.

Since the launch of generative AI, we’ve been conducting extensive research involving CEO interviews and deep dives within leading companies. This work has provided inside knowledge about the success of AI initiatives and has culminated in the book The Humachine. Here are some of these insights.

One AI doesn’t fit all

AI is copyable—and one size doesn’t fit all. What’s not copyable is a unique business model, processes, and integration of humans with that technology.

Our research finds that the massive rush to apply AI technologies to existing business models and old processes will not lead to success.

Spencer Fung, the CEO of global supply chain giant Li & Fung, provides an analogy: “Companies acquiring AI without a new business model is like a company digitizing a horse and carriage—while the competition has created a digital automobile.”

Adding AI to a business model of the past doesn’t lead to competitiveness—it simply solidifies old processes. AI is essential but insufficient in providing a competitive advantage. Before attempting to integrate AI into their businesses, corporate leaders need to first reassess and update their business models.