IBM survey of 2,000 CEOs from 33 countries: 25% of AI initiatives have delivered the expected ROI over the past few years, and 16% have scaled enterprise wide
Just 1 in 4 bets paying off so far — Only a quarter of AI initiatives have delivered the expected return on investment, according to an IBM survey of 2,000 CEOs.
Context & Ripple Effects
Enterprise AI adoption had already broadened, but operational maturity lagged: an earlier survey found that only a minority of organizations had a broad AI strategy, alongside reported project failures limited enterprise-wide AI strategies. More recently, CIOs still expected investment to rise even as many anticipated a delayed return a longer wait for AI returns.
IBM’s CEO survey puts a current scale-and-value benchmark on that gap: expected returns and enterprise-wide deployment remain the exception rather than the default. It matters because it separates willingness to fund AI from the harder work of turning individual initiatives into repeatable business operations.
First-order effects
- For the surveyed companies, only 25% of AI initiatives have met expected ROI, while just 16% have reached enterprise-wide scale; leaders face a clear gap between experimentation, value realization, and deployment.
- IBM gains a data point for positioning AI work around implementation and measurable outcomes rather than adoption alone.
Second-order effects
- Enterprise buyers are likely to apply tighter ROI and scaling criteria to AI projects, favoring deployments tied to defined business processes over broad pilots.
- AI vendors and services providers face greater pressure to show how their products move customers from isolated use cases to governed, repeatable deployment; this reinforces the importance of investment plans paired with longer ROI timelines.
Third-order effects
- If these results persist, enterprise AI competition will shift from model access and pilot volume toward AI industrialization: integration, governance, workflow redesign, and cost accountability become the differentiators.
- The divide between firms that can scale useful AI and those that cannot could widen, though this survey alone does not establish which technologies or operating models produce the difference.
The trend: Enterprise AI is moving from adoption-led spending toward a value-realization test in which scalable workflows and demonstrable returns determine durable investment.