CIOs will rescue 25% of failed business-led AI projects by 2026

Forrester predicts that 25% of CIOs will be tasked with rescuing failed business-led AI projects by 2026, as departments rush to deploy AI without adequate technical support or IT involvement. This trend reflects a broader shift from experimental AI adoption to demanding real operational results, forcing organizations to recognize the critical role of IT leadership in scaling AI successfully.

The big picture: Many organizations adopted a “bottom-up” approach to AI, allowing departments to experiment independently without significant CIO or IT team involvement, creating fragmented usage and inconsistent governance.

Why this matters: As AI moves beyond the “imagination phase” into demanding measurable productivity gains, the technical complexity of successful deployments is exposing the limitations of business-led initiatives that bypassed IT expertise.

What’s driving the failures: Business teams are underestimating the comprehensive technical requirements needed for successful AI implementation.

• “What we’re seeing is they’re just lacking the depth of understanding of everything you need to do from a data perspective, from a hardware perspective, from a quality perspective, from a testing perspective,” says Alek Liskov, chief AI officer at Datalinx AI, a data refinery platform provider.
• Organizations are “cutting corners, trying to rush deployments to production,” leading to projects that become “too costly because you don’t understand the economics while the models start running, or too many defects causing other problems,” according to Forrester’s Mark Moccia.

The cultural challenge: Successful AI integration requires overcoming traditional business-IT disconnects and building collaborative project teams from the start.

• “Start with the tech folks in the room first, before you get much farther,” Liskov advises, noting that business leaders sometimes view IT teams as impediments rather than enablers.
• “I still see many organizations where there’s either a disconnect between business and IT, or there’s lack of speed on the IT side, or perhaps it’s just a lack of trust.”

What CIOs should do: IT leaders need to position themselves as essential partners in AI strategy rather than reactive problem-solvers.

• “AI is just another technology to add to the stack,” says Bill Finner, CIO at Jackson Walker, a large law firm. “Better to embrace it and help the business succeed then to sit back and watch from the bench.”
• CIOs should serve as in-house experts for vetting solutions and controlling costs while educating teams on AI capabilities and workflow integration.

The shifting landscape: Currently, only 39% of AI decision-makers say their CIOs or CTOs lead AI technology strategy, with just 21% leading AI business strategy—percentages Forrester expects to double as organizations recognize IT’s crucial role in building successful AI agents.

What they’re saying: “Most successful AI tools have spread organically, with employees adopting what actually helps them get work done, instead of coming from top-down mandates,” explains David Shim, CEO of Read AI, an AI notetaker provider. “That’s great for innovation, but it also means many organizations now have fragmented AI usage, inconsistent data pipelines, and no centralized governance.”