At a recent gathering of corporate directors, when asked who felt ready to oversee AI, no one raised a hand.
That’s where many boards are today. Awareness is high. The stakes are obvious. But there’s real uncertainty about how to exercise judgment on something that will reshape economics, operating models, and investor expectations.
It’s understandable. Boards are being asked to govern decisions with far-reaching consequences long before outcomes are clear and while the tools and scenarios in play are still evolving. Despite the complexity, the mechanics of strong AI governance remain foundational. Here are five things boards need to get right.
Drive Pace, Purpose, and Priorities
AI will optimize toward whatever is set in front of it. So, while a few big bets are better than a dozen pilots, those bets need to matter. The AI agenda should concentrate on the capabilities and value pools that will shape competitive position—where AI can strengthen differentiation, improve customer economics, or reshape how the company competes.
Boards can help keep that alignment clear. AI priorities must serve the business strategy, not sit beside it. Play devil’s advocate: What would a serious rival or an AI-first entrant try to change over the next few years? How could they use AI to reset customer expectations, cost structures, or speed to market?
AI priorities must serve the business strategy, not sit beside it. Play devil’s advocate: What would a serious rival or an AI-first entrant try to change over the next few years?
Pace is paramount. The most impressive ideas matter only if the company scales them. Boards can help by clarifying which initiatives warrant real investment and which obstacles might slow adoption. Without that pressure, companies accumulate pilots, not advantage.
Protect Strategic Freedom in Technology Decisions
The technology choices being made now will shape the company’s position for years. Decisions about which capabilities to build, which AI partners to engage, how best to use AI agents, and to what degree—plus the technological expenditures that support movement toward an AI-first organization—are difficult to unwind and often outlast the current management team. These choices determine cost trajectories, constrain architecture, and limit where capital can be redirected later.
The board’s role is to make sure management weighs the long-term consequences of these choices. Its job is not to debate tools but rather to be explicit about what each choice commits the company to and what it forecloses. A practical way to do this is to look for one-way doors. When a decision effectively locks the company into a partner ecosystem, a proprietary architecture, or a narrow talent model, boards should ask what alternatives remain and what it would take to reopen them. Modular design, diversified partnerships, and a deliberate balance between internal and external capabilities preserve room to maneuver as the technology landscape evolves.
Look for one-way doors. When a decision could lock the company into a partner ecosystem, ask what alternatives remain and what it would take to reopen them.
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Shape the AI Investment Portfolio
The board’s job is to make sure AI investment is being treated as a portfolio, not a collection of projects. Return expectations should be shaping that mix. How much capital is allocated to near-term performance gains? How much toward transforming the company’s cost structure or operating leverage over time? And how much to support growth avenues that are less certain but strategically important? The deploy–reshape–invent balance needs to be deliberate and grounded in economic logic, not simply in what is easiest to justify.
Boards add the most value by keeping that portfolio logic explicit. They can insist on ROI discipline where outcomes should be clear while ensuring the company doesn’t crowd out the longer-horizon investments that sustain future advantage. Without that balance, AI programs default either to safe incrementalism or scattered experimentation. Neither changes the company’s competitive trajectory.
Be a Growth-Oriented Voice of Reason
Ambition has to be matched by readiness. Is the company equipped to scale AI with the data, systems, and talent it has today? Where are the practical gaps that could slow execution? Surfacing those constraints early is how boards keep enthusiasm from outrunning delivery.
Just as important is making sure the organization has real incentives to close those gaps. AI transformation changes how work gets done, how decisions are made, and what performance looks like. If compensation, evaluation criteria, and governance still reward the legacy model, progress will stall. This is where the remuneration committee has a direct role to play. Aligning leadership incentives with outcomes such as data readiness, adoption of new workflows, and measurable business impact makes the transformation tangible and enforceable.
Boards help determine how much disruption the company is willing to absorb. Leaders who are asked to rewire parts of the business need clear backing to push through short-term disruption in service of longer-term gains. Providing that support, while maintaining discipline on results, is how boards stay growth oriented and grounded at the same time.
Keep Communications Measured and Intentional
AI has raised the stakes in corporate communication. Even casual comments can create expectations the company never intended to set. A single reference to an “aggressive rollout” can be read as a cost target or earnings signal. Efficiency claims can invite pricing pressure from customers. Disclosure requirements have also changed, with SEC rules now requiring companies to identify which annual report statements are generated by AI.
Boards can help by establishing discipline around how AI is discussed externally. Many management teams underestimate how quickly AI-related statements travel or how easily routine updates are interpreted as commitments. Board directors can press management on what is real today, what remains experimental, and what is still uncertain before those messages leave the room.
That discipline matters because stakeholders do want clarity. Employees, investors, and others have a legitimate interest in understanding the company’s ambitions. The task is to be clear without getting ahead of the facts.
Get in the Sandbox and Play
Boards do not need to become fluent in AI. But they can’t govern what they only hear about secondhand.
The most effective boards proactively commit to upskilling. They engage not only with the tools their businesses use but also incorporate AI tools into their own flow of work. Firsthand experience with the technology spread across multiple members can shift the dynamic in the boardroom. It can keep the conversation from leaning too heavily on one or two tech-savvy voices.
Firsthand experience with AI can keep the conversation from leaning too heavily on one or two tech-savvy voices.
Over time, boards will see more immersive options—digital twins, richer simulations, stronger forecasting support. For now, keep it simple. Keep AI close enough that it stops being an abstraction and becomes something the board can read, test, and discuss with confidence.
AI will change shape, pace, and promise year to year. The job of the board is steadier. Stay close to where value is shifting. Keep the agenda focused on the few moves that matter. Make sure the organization has room to pivot, the judgment to communicate wisely, and the license to lead. If those pillars hold, the company will be able to absorb whatever comes next and convert it into progress.
