AI Spending Skyrockets, Yet C-Suite Unsure Who's in Charge
Source: Fortune. Casualplayhub News adds summary, context, and editorial framing while linking back to the original report.
Everyone agrees that someone is steering the corporate AI strategy. The problem? A significant number of executives have no idea who that person is. A new Pearl Meyer survey, released Thursday, reveals a glaring leadership vacuum at the top of many companies. Only 34% of C-suite executives said it is consistently clear which executive or team makes the final calls on AI—the lowest percentage among all groups polled. Among board members, that figure rose to 53%, and among senior managers and professionals below the C-level, it climbed even higher to 57%. The irony is sharp: the executives who are actually implementing AI on the ground are the least certain that anyone is truly owning the decisions and outcomes. Those farthest from the messy work of deployment are more likely to believe the matter is settled.
The survey, part of Pearl Meyer's Q2 2026 Market Intelligence Survey, polled 116 board members, CEOs, C-suite executives, and senior managers in May and June. The results were shared exclusively with Fortune ahead of their Thursday release. They come at a high-stakes moment. Total AI spending, including capital expenditures on infrastructure, is projected to reach $2.5 trillion this year—a 44% increase over 2025, according to research firm Gartner. Next year, spending is expected to climb to $3.3 trillion. With that kind of money on the line, CEOs know that falling behind competitors—or failing to deliver results internally—could cost them their jobs. A separate survey of 900 CEOs published in May found that 80% of U.S. CEOs believe their own position is at risk if their AI initiatives stall, while 81% think a fellow CEO will be fired 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 states. "Additional investment without clear ownership will only widen that gap." Brad Jayne, a principal at Pearl Meyer and co-author of the study, noted that expectations for AI's impact don't seem tied to actual progress. Confidence that AI will deliver significant gains within 18 months holds steady at about 50% among leaders, regardless of whether their companies are in the pilot phase, experimenting, deploying at enterprise scale, or haven't even started. "There's an impact-versus-speed tension," Jayne said. Handing out licenses for tools like ChatGPT or Copilot is quick and easy, he explained. But building robust systems around them, pushing them through the organization, and ensuring they don't make errors—that takes much longer.
CEOs may also be overly optimistic about their employees' capacity for change. When asked if workers could handle additional organizational change—such as AI implementation—without feeling stretched too thin, 63% of CEOs said yes. But only 33% of the C-suite and 40% of non-C-suite executives agreed. Boards, meanwhile, seem disconnected from the magnitude of transformation ahead. 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 answered yes. Yet only 42% of directors agreed. "That's an alarm bell for me," Jayne said, particularly when combined with the change-fatigue response. "The board is basically saying, 'We're good. We've made investments, we're structured right, go make changes,'" Jayne observed. "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 concern is what happens when spending needs to be justified a year from now. If boards and management teams can't connect AI spending to outcomes that investors can recognize and value, trouble looms. "I worry about finger pointing," he said. The blame could fall on culture, learning agility, or insufficient experimentation with AI tools. "It might come to some turnover," Jayne added. "I think we're in for a bumpy ride." The survey's findings underscore a fundamental challenge: as companies pour trillions into AI, the lack of clear ownership and alignment between the boardroom and the front lines threatens to undermine the very returns they hope to achieve.
Article commentary
The Pearl Meyer survey paints a vivid picture of organizational dissonance in the age of AI. While companies are funneling unprecedented sums into artificial intelligence—$2.5 trillion this year alone—the C-suite remains surprisingly unsure about who is actually calling the shots. This lack of clarity is not just a governance hiccup; it is a structural vulnerability that could amplify the risks already inherent in such massive investments. The data reveals a troubling paradox: those closest to the implementation—senior managers and professionals below the C-level—are the most confident that ownership is clear, yet the C-suite, which bears ultimate responsibility, is the least certain. This suggests that accountability may be diffused or delegated without clear authority, creating a fertile ground for misaligned expectations and execution failures. One of the most striking findings is the disconnect between CEOs and their boards. While 88% of CEOs foresee significant operational changes within three years to achieve strategic goals, only 42% of directors agree. This gap indicates that boards may not fully grasp the scale of transformation AI demands—or they may be underestimating the disruption required. When combined with the finding that 63% of CEOs believe employees can handle more change, while only a third of the C-suite agrees, it becomes clear that leadership is operating with dangerously different assumptions. The risk is that boards will continue to approve spending without understanding the cultural and operational shifts needed, while management struggles to implement change under the weight of unrealistic expectations. The "impact-versus-speed tension" that Brad Jayne describes is a critical insight. Deploying AI tools like ChatGPT or Copilot is deceptively simple, but transforming them into enterprise-grade systems that drive measurable value is a slow, complex process. The survey shows that confidence in AI's near-term impact remains high regardless of a company's maturity in AI adoption—a sign that optimism may be decoupled from reality. This could lead to a rude awakening when the promised returns fail to materialize within the expected 18-month window. The pressure on CEOs is immense: 80% fear for their jobs if AI projects falter, and 81% expect a peer to be ousted over an AI crisis. Such anxiety can drive hasty decisions, further muddying the waters of accountability. Another layer of concern is the change-fatigue disconnect. Employees are already stretched thin, and the C-suite acknowledges this, but CEOs remain optimistic. This mismatch suggests that top leadership may be out of touch with the day-to-day strain on their teams. Jayne rightly flags the board's apparent complacency as an alarm bell. If boards believe the company is already structured for success, they may resist the deeper organizational changes that management knows are necessary. The result could be a cycle of underinvestment in change management, leading to failed AI initiatives and eventual finger-pointing. Looking ahead, the key challenge will be bridging these gaps. Companies need to establish clear AI governance structures that define ownership at the C-suite level, align board understanding with management's reality, and honestly assess the organization's capacity for change. The current state—where ambiguity reigns and optimism is untethered from progress—is a recipe for costly missteps. As Jayne warns, we may be in for a bumpy ride. The question is whether companies will learn to steer before the turbulence becomes a crash.