Sixty-one percent of chief executives say their boards are pushing artificial intelligence transformation too quickly, according to a global survey of 625 corporate leaders published by Boston Consulting Group. The research, titled Split Decisions, polled 351 CEOs and 274 board members at companies generating at least $100 million in annual revenue. It reveals a consistent pattern: boards and CEOs agree that AI matters strategically, but they diverge sharply on the appropriate pace of deployment, the depth of board understanding, and how much of a CEO's performance evaluation now depends on delivering returns from AI.
The findings arrive at a moment when AI FOMO (fear of missing out) has become a dominant force in corporate boardrooms. More than half of the CEOs surveyed said that hype surrounding artificial intelligence is distorting their boards' judgment. Nearly 40 percent reported that their boards lack an informed view of how AI is reshaping growth strategy. One in three said their board overestimates the human capabilities that AI can replace. These perceptions create a tension that threatens to misdirect investments and undermine long-term competitiveness.
The Confidence Gap Between CEOs and Board Members
The survey's most striking finding is the disconnect between how board members rate their own AI knowledge and how their CEOs rate it. Three-quarters of board members said their AI understanding is on par with or ahead of their peers. CEOs were far less impressed: less than two-thirds of CEOs agreed with that self-assessment. The implication is that many boards are making consequential decisions about AI strategy based on knowledge their chief executives consider inadequate. This gap matters because board members typically approve AI budgets and set strategic direction. If they misunderstand the technology's capabilities and limitations, they risk approving overly aggressive or ill-timed initiatives.
BCG's Julie Bedard, a managing director and partner, argued that the gap can be closed if CEOs take direct responsibility for board education. Rather than delegating AI briefings to a chief technology officer or an outside consultant, CEOs should personally lead upskilling sessions that demonstrate what current AI tools can and cannot do. They should frame AI in terms that distinguish between tasks where the technology substitutes for humans and tasks where it complements them. This distinction is more important than it sounds. Boards that treat AI as a wholesale replacement for human labor are likely to push for faster, broader deployment than the technology can currently support. Boards that understand AI as a complement to human work are more likely to approve investments scoped to realistic outcomes. The survey suggests that too many boards are in the first camp, and that the consequences of FOMO-driven investment decisions are becoming harder to ignore.
The Accountability Mismatch
The survey also exposed a gap in how CEOs and boards perceive accountability for AI results. CEOs estimated that 35 percent of their performance evaluation now depends on delivering AI-related returns on investment. Board members put the figure at 27 percent. The eight-percentage-point difference suggests that CEOs feel more pressure to show AI results than their boards realize they are applying. This mismatch shapes behavior in important ways. A CEO who believes more than a third of their evaluation hinges on AI outcomes has a strong incentive to prioritize AI projects, even if those projects are premature or poorly scoped. A board that believes the figure is lower may not understand why its CEO is resisting calls to move faster, or may underestimate the operational risk of accelerating deployment to meet perceived expectations.
Judith Wallenstein, BCG's managing director and senior partner who leads its global CEO Advisory practice, emphasized that CEOs need to bring their boards along on the same learning journey they have taken, but compressed and focused on building genuine understanding rather than surface-level awareness. The engineering and operational realities of AI deployment are considerably messier than the boardroom presentations that often precede investment decisions. Real-world AI projects require data infrastructure, model governance, and continuous iteration—factors that are easily glossed over in a quarterly update.
What the Survey Does Not Say
It is worth noting what the research does not cover. The survey does not measure whether the CEOs who say their boards are rushing are themselves correct in their caution, or whether some boards are right to push harder. In certain industries—such as technology, financial services, or e-commerce—faster AI adoption may be exactly the right strategy. In those cases, CEO resistance could reflect organizational inertia rather than sound judgment. The data captures a perception gap, not a verdict on who is right.
The survey also does not break down results by industry, geography, or company size beyond the $100 million revenue threshold, which limits the conclusions that can be drawn about specific sectors. A board pushing AI transformation at a financial services firm faces a very different risk profile—including regulatory compliance, data privacy, and systemic stability—compared to a board doing the same at a manufacturing company, where automation and predictive maintenance are more straightforward. The survey treats all contexts identically, which may obscure important nuances.
What the research does establish is that the most senior leaders at large companies are not aligned on the most consequential technology investment of the current era. Approximately 80 percent of both CEOs and board members agreed that prospective board candidates should be required to demonstrate a measurable understanding of how AI can reshape their industry. This finding suggests that both groups recognize the knowledge gap, even if they disagree on its severity. It also points to a future where AI literacy becomes a prerequisite for board membership, much like financial literacy is today.
The Harder Question: Governance and Technical Fluency
The deeper issue the survey raises is whether traditional board governance is suited to decisions about AI at all. Boards typically meet a handful of times per year, rely on management presentations for information, and are composed of members whose primary expertise may lie in finance, regulation, or sector-specific operations rather than technology. That structure worked well when the pace of technological change allowed for quarterly deliberation. It is less clear that it works when the questions that matter most about AI require technical fluency that most board members do not possess.
BCG's recommendation—that CEOs should personally educate their boards—is practical but also reveals a structural tension. If the chief executive is the primary source of a board's AI understanding, the board's ability to independently evaluate the CEO's AI strategy is compromised. A board that relies on the CEO for education may be less likely to challenge assumptions or ask tough questions about timelines, budgets, and risk management. The survey does not propose a solution to this tension, but it does make the tension visible. Some experts suggest that companies should consider adding a dedicated technology director or an AI advisory committee to the board, but that idea remains controversial and is not yet widely adopted.
Another layer worth exploring is the broader historical context. Corporate enthusiasm for AI has waxed and waned over the past decade, with earlier waves of machine learning and automation often failing to meet expectations. The current wave, powered by generative AI and large language models, has rekindled FOMO, but the fundamental challenges of data quality, model explainability, and integration with legacy systems remain unsolved. Boards that lack deep technical understanding may not appreciate that these challenges are not merely implementation details—they are strategic risks that can derail an entire transformation effort.
For companies trying to scale AI in the coming years, the message is clear: alignment at the top is not optional. Boards that push too fast risk approving projects that fail to deliver returns. CEOs that move too slowly risk losing competitive ground. And for both groups, the temptation to let AI substitute for clear thinking rather than support it is a risk that no survey can fully quantify.