The report, titled You Can't Scale AI on Ambition Alone, surveyed 500 business leaders across the U.S., UK, and DACH region. It paints a picture of an industry that has successfully pushed past the initial hype cycle only to encounter a stubborn reality: the infrastructure needed to measure AI’s financial impact is largely missing. Half of the surveyed companies rely on inconsistent or informal methods to track outcomes, leaving them unable to confirm whether their AI tools actually move the needle on productivity or profitability.

This lack of quantification is compounded by a disconnect between the C-suite and the shop floor. Executives are twice as likely as senior managers to claim advanced AI adoption, suggesting that top-down strategy is currently outpacing the actual technical capabilities of their teams. Despite this, 44% of manufacturers are doubling down on AI deployment specifically to hedge against tariff pressures and rising compliance costs. Mike Sabin, CEO of Revalize, warns that this reliance on assumption over evidence is unsustainable. He argues that the companies most likely to survive this shift are those that stop treating AI as a generic fix-all and start managing it as a disciplined investment tied to specific, measurable operational hurdles.