Enterprise AI Hits Reality Check as MIT Warns 95% of Projects Fail to Deliver Revenue Gains
But the long view remains bullish. Nearly 88% of enterprises plan to increase AI investment in 2026, signalling that despite the stumbles, strategic appetite for AI remains strong. What separates success from stagnation? Focus, governance and clean data. Leaders at Solvd and Tessell stress the need for targeted objectives—such as reducing churn or streamlining HR—and warn that outdated tech stacks and “dirty data” are where AI dreams go to die.
Compliance is fast becoming a board-level concern. Regulatory crackdowns on “AI-washing” and tougher rules from the EU and US states mean businesses must train up governance teams, especially in regulated sectors. The stakes are high: the so-called “verification tax” on staff to double-check AI outputs is now seen as essential insurance against reputational and regulatory risk.
Still, the Wharton Human-AI Research group finds 82% of enterprise leaders are already using AI weekly, with daily usage rising. Nearly three-quarters report positive ROI, and most expect meaningful returns within two to three years. As we approach 2026, the enterprise AI shift is less about hype and more about hardened discipline. Those who modernise infrastructure, align AI with business outcomes, and stay ahead on compliance will define the next era of business performance.
For the UK, this is a pivotal window to lead in responsible enterprise AI. The challenge isn’t enthusiasm—it’s execution.
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