About one in four senior business leaders at Global 2000 companies have already paused or abandoned an AI deployment, according to a Cognizant survey of 1,100 executives and 100 startup leaders across 10 industries. The figure lines up with a recurring finding in independent enterprise AI research: most large-company AI projects stall well before they reach production scale, and the projects that do ship tend to share a common foundation.
The press release leads with $4.7 trillion in "untapped AI value" across the Global 2000. That number is a constructed aggregate. Cognizant's per-organization estimate is about $2 billion in unrealized cost savings and revenue opportunity; the $4.7 trillion is that figure multiplied across a synthetic Global 2000 universe. The press release does not include a methodology document, and the construction is not independently verifiable. Read it as marketing, not measurement.
The findings in the report that survive external scrutiny are the abandonment rate, the performance gap, and the infrastructure-maturity effect. Cognizant says the highest- and lowest-performing organizations that pair mature tech infrastructure with a fundamentals-first AI investment strategy are separated by 31%. Organizations with immature infrastructure and broad AI investment are 60% more likely to abandon a deployment than those with the same infrastructure who invest in AI fundamentals first. And organizations with strong data foundations hold a 27% productivity advantage over those still working to improve theirs. The release frames the 31% gap as an "AI Builder dividend." The phrase is a marketing term, not a discovery, and the framing aligns cleanly with Cognizant's services catalog. The underlying signal — that infrastructure maturity and disciplined investment sequencing drive AI outcomes more than model choice alone — is not vendor-only. Independent research on enterprise AI deployment has produced similar patterns on infrastructure dependence and project abandonment, including work from McKinsey, Stanford HAI's AI Index, and MIT Sloan.
Cognizant (NASDAQ: CTSH) is an AI services vendor with a direct commercial interest in the execution-gap narrative. The study was released on 2026-06-15 via PR Newswire. None of that disqualifies the data, but it does change how a reader should hold it.
The takeaway for readers: the next vendor study that lands in your inbox with a multi-trillion-dollar AI opportunity will almost certainly be built the same way. A per-organization estimate, multiplied by a synthetic universe, presented without methodology. The numbers worth tracking are independently corroborated: the deployment-abandonment rate, the infrastructure-maturity effect, and the productivity differential tied to data foundations. Those move slowly. They do not need a press release.