Only 34% of C-suite executives in a new Pearl Meyer survey said it’s consistently clear which executive or team makes calls about AI, which was the lowest of all the cohorts polled. Among corporate board members, the figure rose to 53%. But when the question was asked of senior managers and professionals below the C-level, the figure rose even higher to 57%. 

Essentially, the group of executives likely to be blocking and tackling on-the-ground AI implementation are the least convinced that anyone is clearly owning the decisions and results. Those who are furthest away from owning the messiness of implementation, are more likely to feel the matter is settled. The survey found 78% of executives below the C-suite report that their companies have the senior talent required to effectively implement and oversee AI across the whole company. 

Significant gaps between the uppermost rungs at companies and other executives run through much of Pearl Meyer’s Q2 2026 Market Intelligence Survey. The poll of 116 board members, CEOs, C-suite execs, and senior managers below them was conducted in May and June and shared exclusively with Fortune ahead of its release on Thursday. 

The results, which show that AI deployment isn’t going as smoothly as some CEOs had hoped, comes at a high-stakes and expensive moment. Total AI spending, including capital expenditures on AI infrastructure, is poised to reach $2.5 trillion this year, a 44% increase in spending over last year, according to research and advisory firm Gartner. Next year spending is projected to rise to $3.3 trillion, the firm found. At that level of investment, CEOs know their heads could be on the chopping block if they fall behind relative to competitors and if they fail to deliver at their own companies. A survey of 900 CEOs published in May revealed that 80% of U.S. CEOs think their job is at risk if their AI projects wither on the vine, while 81% believe a fellow CEO will be ousted due to an AI failure or crisis. 

“Ambition for AI outcomes is currently outpacing the leadership structure needed to deliver on them,” the Pearl Meyer study, published on Thursday, states. “Additional investment without clear ownership will only widen that gap.”

But at this point, expectations for how much of an impact AI will have on individual companies doesn’t seem rooted in how much progress has been made in implementing it. Brad Jayne, a principal at Pearl Meyer and co-author of the study, said confidence that AI will deliver significant gains within 18 months holds at about 50% among leaders of companies at every stage of maturity including the pilot phase, experimentation, enterprise-level deployment, and companies that haven’t started anything yet. 

“There’s an impact-versus-speed tension,” said Jayne. Handing out licenses for ChatGPT or Copilot is quick and easy, he said. “Building big systems around that and pushing them through the organization and making sure it’s not making errors, that takes a lot longer.”

CEOs may also be overly optimistic when it comes to how close to burnout their employees are. When asked if employees could tackle additional organizational change without feeling stretched too thin, with AI implementation as an example, 63% of CEOs responded affirmatively, with only 33% of the C-suite and 40% of non-C-suite executives in agreement. 

Boards, for their part, may be in the dark as to how much more change is coming. Asked whether achieving strategic goals will require significant changes to how the organization operates within three years, 88% of CEOs and 79% of C-suite executives said yes. Only 42% of directors agreed. 

Coupled with the change-fatigue response, said Jayne, “that’s an alarm bell for me.”

“The board is basically saying, ‘We’re good. We’ve made investments, we’re structured right, go make changes,’” said Jayne. “And the management team is saying, ‘Whoa, whoa, whoa. In order to be effective here and get our strategy done, we’re going to have to make big changes in how we operate together.’”

Jayne’s worry is about what happens when spending has to be justified in a year. If boards and management teams can’t successfully connect AI spending to outcomes investors can recognize and appreciate, there could be problems. 

“I worry about finger pointing,” said Jayne. It could be culture, learning agility, or insufficient experimentation with AI tools. 

“It might come to some turnover,” said Jayne. “I think we’re in for a bumpy ride.”