AI is becoming embedded in strategy, operations, and risk.
Lalena Kennedy via Canva
By C200 Member Bridget Ross
In many boardrooms, AI is now a regular agenda item. Directors are reviewing use cases and hearing updates, but the more important question is how AI is shaping the decisions they are being asked to evaluate, and what that means for governance.
As adoption accelerates across industries, AI is becoming embedded in strategy, operations, and risk. Yet governance is still catching up. Research shows that only about a quarter of organizations report having a fully implemented AI governance program.
Boards are still responsible for evaluating proposals, assessing risk, and approving direction. What has changed is the level of insight required to carry it out effectively.
Governance has traditionally focused on reviewing the final proposal and its supporting analysis. Today, that approach needs to go further. Directors need to understand how decisions are formed.
Boards rely on structure to do their work effectively. Agendas, pre-read materials, and formal processes create discipline, support informed discussion, and ensure accountability. But this structure is designed to organize information, not to reveal how that information was created.
When analysis is shaped earlier in the process, the board may receive a clear and well-supported proposal without full context into the inputs, assumptions, or trade-offs behind it. This is where governance starts to break down. The issue is not the quality of the materials, but the level of insight they provide into how the conclusion was reached.
As expectations for governance evolve, this issue is becoming more visible. Recent guidance from INSEAD and KPMG underscores that boards are now expected to demonstrate informed oversight of how initiatives are developed, deployed, and monitored, reinforcing the need for greater transparency into how proposals are generated and validated, not just the outcomes presented.
Alongside this, AI is expanding the volume of information available to organizations. Leadership teams can access deeper analysis, explore more scenarios, and generate outputs far more quickly than ever before. In theory, this should lead to better decisions. In practice, it often has the opposite effect.
Information overload becomes more pronounced as data volume increases. It becomes harder to identify which inputs should drive the decision and which simply add noise.
Boards encounter this directly. Materials are more detailed and more data-rich, yet that additional depth does not always lead to clearer direction. In some cases, it creates a sense of completeness that is not supported by the underlying insight.
Effective governance depends less on the quantity of information presented and more on the discipline applied in evaluating it. Filtering inputs, challenging assumptions, and maintaining focus on the few issues that drive outcomes become more important as the volume increases.
AI can support that process when it is used to narrow attention rather than expand it. Clarity remains a function of judgment—deciding what matters, what does not, and where to direct attention.
AI is accelerating how quickly decisions move through organizations, shortening the time between initial analysis and final proposal. What once unfolded over days or weeks can now come together much faster.
That compression leaves less room to test assumptions, challenge conclusions, or work through competing views. Decisions that might have been examined across multiple discussions can move forward with fewer opportunities for scrutiny.
The responsibility of the board does not change, but the conditions under which it is exercised do. As timelines narrow, maintaining the same level of evaluation requires more intention. The question is not whether decisions are moving faster. It is whether the evaluation keeps pace.
AI is now embedded in how decisions are developed across strategy, risk, and operations, and that is unlikely to change. What it does change is what boards need to see in order to do their job effectively.
Boards remain responsible for oversight, for evaluating proposals, and for the decisions they approve. Accountability does not shift. What changes is the level of visibility and discipline required to support that responsibility.
Evaluating a proposal requires more than reviewing the conclusion. It requires understanding the inputs, assumptions, and points of judgment that shaped it. Without that context, it becomes harder to assess risk or weigh trade-offs with confidence.
In practice, this calls for a more focused approach to how boards engage with what is in front of them. A small number of consistent questions can help maintain that focus:
These questions do not require technical expertise. They require attention to how decisions are developed and a willingness to examine what sits behind them. AI can make recommendations faster. It does not strengthen the judgment applied to them.
C200 member Bridget Ross is an accomplished MedTech executive with expertise in innovation and market creation. She currently serves as a Board Director and Chair of the Nominating and Corporate Governance Committee for LeMaitre Vascular Inc. (NASDAQ: LMAT), and as CEO and Board Director of ChroniSense Medical (now Polso), a digital health company transforming remote patient care and advancing clinical research. She has mentored numerous CEOs through the IGNITE Accelerator and the Canadian Technology Accelerator in Boston. Previously, she had a successful career at Johnson & Johnson, guiding innovations from R&D to market.
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