AI is no longer a topic that belongs only to the technology team. It now shapes decisions about competition, organization, capital allocation, and risk, giving boards a direct role in how companies use it and control it.
That shift raises a practical question: Can your board answer the questions that come with AI oversight? The answers matter because companies now face pressure from investors, regulators, shareholders, and their own financial results. Here are seven questions likely to sit at the center of board discussions through 2026.
1. Is AI on every board agenda?
Only 26% of boards discuss AI at every meeting. That number matters because organizations that keep AI on every agenda see higher returns than organizations that treat it as an occasional item.
The gap is clear among companies grouped by their results. In high-ROI organizations, 63% of boards put AI on every agenda. In the low-ROI group, only 13% do. The difference does not prove that meeting frequency alone creates better results, but it shows how closely regular board attention lines up with AI performance.
A board that discusses AI only when a major launch, failure, or investment appears may miss how the technology affects the rest of the business. Regular discussion gives directors a place to examine competition, organization, capital allocation, and risk before those issues become urgent.
2. What does AI mean for the company’s biggest risks?
AI and machine learning became a top-issue concern for 40% of respondents in Nasdaq’s Governance Pulse survey, up from 19% two years earlier. That change shows how fast AI moved from a technology question to a governance concern.
The filings tell a similar story. In 2026, 72% of S&P 500 companies identify AI as a material risk in their Form 10-K filings. When a risk appears in that filing, directors need to understand what the company is saying about it and how the business manages it.
The board’s question is not simply whether AI creates risk. It is whether the company has identified the risks tied to its AI use and placed those risks within a system that directors can monitor.
3. Who oversees AI at board level?
Roughly 8% of the 3,048 Russell 3000 and S&P 500 companies reviewed by Institutional Shareholder Services disclose any board-level AI oversight. That leaves a wide gap between the number of companies naming AI as a material risk and the number disclosing board oversight.
Board members reading these figures, along with attention from Glass Lewis, are more likely to ask who owns AI oversight and how that responsibility reaches the board. The answer needs to connect executive decisions, risk monitoring, and the company’s public statements.
Oversight does not end when the board assigns responsibility. Directors also need a way to monitor whether the system works, especially as AI decisions spread beyond the technology team.
4. Could directors face personal liability?
Under Delaware’s Caremark doctrine, directors can face personal liability for failing to implement or monitor oversight systems. That legal framework gives AI oversight a direct connection to board duties.
The question for directors is plain: does the company have an oversight system that addresses AI, and does the board monitor it? A board that treats AI as someone else’s responsibility may struggle to answer when a problem reaches the company’s filings, finances, or reputation.
This does not turn every AI mistake into director liability. It does make oversight systems and monitoring important parts of the board’s work.
5. Are the company’s AI claims accurate?
Shareholder suits have targeted companies accused of overstating AI capabilities or understating AI costs and risks. That gives boards another question to ask before approving public claims: does the company’s description match what its AI can do, what it costs, and what risks it carries?
Accuracy matters on both sides. A company can create trouble by presenting AI as more capable than it is, but it can also create trouble by leaving out costs and risks that investors need to understand.
6. Who makes the final AI decisions?
Duane Tursi said, “72% of CEOs are now directly responsible for AI decisions in their companies,” but “only 15% are generating meaningful value from it.” Those figures place the responsibility at the executive level while showing how difficult it remains to turn responsibility into results.
Boards should ask how AI decisions move from the CEO to the rest of the organization, and whether those decisions connect to competition, organization, capital allocation, and risk. AI has moved beyond the technology team, so a narrow technology review cannot cover the full business impact.
7. What would meaningful value look like?
The final question is not whether a company uses AI. It is whether the company can explain the value it expects and show how leaders judge that value.
The contrast between 72% of CEOs holding direct responsibility and only 15% generating meaningful value shows why this question belongs in the boardroom. Responsibility without a clear view of results leaves directors with no firm way to judge progress.
Andrew Lovell, Rajoshi Ghosh, Duane Tursi, Boston Consulting Group, Protiviti, and BoardProspects are part of the wider discussion surrounding AI, leadership, and governance. The core issue remains simple: boards need regular, informed oversight before AI decisions become legal, financial, or strategic problems.
By late 2025 and into 2026, AI had become a governance issue rather than a side conversation. Boards that keep asking these questions can connect oversight to business results. Boards that wait for a crisis may find that the questions arrive with fewer good answers.
Based on
- 7 questions your board will ask about AI before you’re ready to answer them — aiacceleratorinstitute.com
- AI Is Becoming An Insurance Board Issue — forbes.com
- Why In 2027 Every CEO Must Operate Like An AI Strategist — forbes.com
- The Benefits And Risks Every Business Leader Needs To Understand About AI — forbes.com
