AI in the Boardroom: What Every Director Should Be Asking

The traditional board model depends heavily on information prepared, filtered, and presented by management. Directors may receive extensive reports, financial disclosures, and committee materials, but their ability to independently test assumptions is often limited by time and access to information.

AI presents an opportunity to change that relationship.

Rajgopal suggests that AI could become the "11th seat in the room," offering directors an additional source of analysis and perspective.

Consider the audit committee. AI could help directors examine an organization's annual financial disclosures alongside competitors' disclosures, identify potentially controversial accounting treatments, and evaluate questions raised by analysts or short sellers.

Instead of relying exclusively on management's interpretation, directors could arrive at meetings with independently developed questions and alternative perspectives.

Curran sees this as part of a broader challenge facing corporate governance.

“Information is now widely available because of AI, and the governance structures that are in place simply are not fit for purpose to address that,” he observes.

The opportunity is not to replace management's expertise or directors' judgment. It is to strengthen independent inquiry and make oversight more informed.

The question for directors: Where are we relying too heavily on management's interpretation of information, and how could AI help us independently test the assumptions behind major decisions?

AI's potential extends beyond financial analysis. Rajgopal outlines several ways the technology could help directors reconsider how board committees approach their work.

For compensation committees, the opportunity begins with a fundamental question: Does executive compensation actually support the organization's strategy?

Rather than starting with lengthy consultant reports and peer-group comparisons, directors could use AI to explore compensation design from first principles. What outcomes does the company need to achieve? Which performance measures reflect those priorities? And what incentives are most likely to encourage the desired behaviors?

For nominating and governance committees, AI could support a similarly forward-looking assessment.

Instead of focusing primarily on replacing departing directors, boards could examine the capabilities they will need over the next five to ten years, compare those requirements with current board composition, and identify gaps.

These applications suggest that AI's value may lie as much in challenging established processes as in making existing ones more efficient.

The question for directors: Are we using AI simply to process existing board materials faster, or could it help us reconsider the assumptions behind committee decisions?

Where should responsibility for AI oversight sit within the board?

For many organizations, the instinct may be to assign it to the audit committee, which already oversees financial reporting, internal controls, and significant risks.

Curran questions whether that approach adequately reflects AI's strategic implications.

“The audit committee is not a strategic committee,” he argues, emphasizing that its essential role in reviewing and pressure-testing information differs from overseeing initiatives that require investment and organizational change.

AI raises questions about competitive advantage, business models, workforce capabilities, and long-term strategy. Those considerations may require different expertise and more direct engagement with the people implementing the technology.

Both Rajgopal and Curran raise the possibility of a dedicated AI and technology committee, although the broader issue is whether boards have the knowledge and processes required for effective oversight.

Curran also challenges traditional assumptions about whose expertise belongs in the boardroom. Employees with direct knowledge of AI systems may be better positioned to explain their capabilities and limitations than more senior executives who receive the information secondhand.

The governance question therefore extends beyond committee assignments to how information and expertise reach directors.

The question for directors: Do our governance structures provide the right expertise, accountability, and access to information for meaningful AI oversight?

Board agendas have traditionally devoted substantial attention to financial results, regulatory obligations, and compliance. These responsibilities remain essential, but they can leave limited room for exploring alternative futures.

AI could help change the balance.

Rajgopal points to the value of scenario planning, noting that although plans will inevitably prove imperfect, the process of planning remains valuable.

With AI, organizations can explore a wider range of potential outcomes, challenge assumptions, and test strategic choices without relying exclusively on time-intensive consulting exercises. Curran emphasizes an important distinction: management develops strategy, while boards review, challenge, and approve it.

AI could strengthen that relationship by enabling management to present more extensively tested recommendations. For example, an acquisition proposal could be evaluated against a wider range of financial, operational, and competitive scenarios before reaching the board.

For directors, the value is not necessarily having more information. It is having greater visibility into the alternatives considered, assumptions tested, and risks that could change a decision.

The question for directors: Are we asking management to show us enough alternative scenarios, and what would cause us to reconsider our current strategy?

AI adoption is not simply a technology decision. It raises questions about investment priorities, organizational capabilities, workforce implications, and accountability.

When assessing organizational readiness, Rajgopal returns to the fundamentals of strategy and governance.

What is the organization's competitive advantage? How does AI contribute to it? How should the return on AI investments be evaluated?

From there, directors need clear plans, performance indicators, reporting mechanisms, and follow-up processes.

As Rajgopal emphasizes, the board's responsibility is to govern, not operate the company.

Curran adds that directors must also recognize the limits of their own knowledge. Effective oversight requires candid conversations, access to relevant expertise, and a willingness to acknowledge uncertainty.

This becomes particularly important when evaluating AI initiatives whose financial returns may be difficult to quantify and whose effects extend across the organization.

Boards must also consider the implications for employees and other stakeholders, including whether the organization's actions remain consistent with its stated values.

The question for directors: Can management clearly explain where AI creates business value, how success will be measured, and what organizational changes are required to achieve it?

AI presents an opportunity to reconsider how directors obtain information, challenge assumptions, and exercise independent judgment.

The technology alone will not resolve longstanding governance limitations. Boards still need the expertise to interpret information, the willingness to ask difficult questions, and the discipline to distinguish strategic opportunities from technological enthusiasm.

But directors who approach AI solely as another risk to monitor may overlook its potential to strengthen the board's own effectiveness.

The question is no longer just how boards should oversee AI. It is how AI could help boards provide better oversight.