The boardroom is no stranger to disruption, but few forces are transforming business as swiftly or profoundly as artificial intelligence. From generative AI tools to predictive analytics, these technologies are reshaping business from within (operations) and without (the market and competitive landscape) and having a profound impact on nearly every organization’s strategy.  

Unsurprisingly, AI is a difficult subject for most boards to get their hands around. Not only is it new, it is moving at breakneck pace. Every week sees new advances in and uses for AI, and if you aren’t working, which most board members are not, you aren’t likely to be using AI every day and evolving your understanding of it in sync with how your company is using it. Regulations are few and far from keeping pace; at this point they offer few guideposts for oversight of AI. Boards are behind the 8-ball. The good news is they know it.  

Boards graded their performance on AI Oversight as a 73 on a scale of 100, roughly a C-

AI Oversight topics were the absolute lowest scorers in the 2025 Boardspan Benchmark, which is built from the aggregated data collected from all boards that participated in the Boardspan Board Performance Assessment over the previous year. Boards graded their performance on AI Oversight as a 73 on a scale of 100, roughly a C- in the letter-grade system. (The highest scoring topic in the 2025 Benchmark received 95 out of a 100, for a solid A, while the mean score for all topics was 87, or about a B+.)   

The 2024-2025 assessment season was the first in which Boardspan included questions on AI Oversight, and boards were candid about their progress: While many are actively seeking to educate themselves to understand the implications, ethics, risks, competitive impact and compliance issues, few have fully established what they consider to be appropriate mechanisms and processes for board oversight of this era-defining innovation.  

Boards of companies that have already baked AI into their product offerings, mainly software companies, tend to be much farther along the AI Oversight learning curve and feeling more confident in their performance.  We would venture to guess that over the next 12 months boards will dramatically increase their knowledge and activity around AI, and it’s likely that next year’s Benchmark scores for AI Oversight topics will see an uptick. 

The gold standard of AI oversight is yet to be defined, but will surely require a strong working knowledge of AI’s strategic, ethical, and operational dimensions as well as board structures that encourage that knowledge to be consistently applied across fiduciary responsibilities. Ideally, the board will ensure that AI initiatives align with the company’s mission and values and that AI investments drive measurable outcomes, while also anticipating the risks of bias, misuse, and unintended consequences.  

High-performing boards will actively engage with management on AI-driven innovation, foster a culture of responsible experimentation, and advocate for transparency and human oversight. They will also need to ensure clear accountability structures and compliance with evolving regulations. Ultimately, boards will be working to seamlessly integrate AI Oversight into broader enterprise risk and strategy discussions, not as an add-on, but as a core competency. 

By committing to structured learning, clear oversight roles, and a deep curiosity about AI’s implications, boards can evolve their governance capabilities in step with this transformative technology.  

Boardspan consultants have spent many hours this year advising our board clients on AI Oversight and how to approach it. Here are a few trends we have identified. 

Most boards want to hear more from the management team. Two key questions to start with: 

• How is AI being leveraged for operational efficiencies?  
• How can it be leveraged to be a differentiator against competitors?  

Best Practice: Embed AI into the board’s regular rhythm through recurring agenda items, standing committee assignments, and clear expectations for reporting from management. This normalizes oversight and avoids treating AI as an occasional or one-off topic.  

Few boards are satisfied with their current levels of AI knowledge and expertise and are seeking to uplevel. Common plans include: 

• Regular presentations and updates from management and/or outside experts that examine how AI is being applied, or could be applied, to the relevant landscape  
• Continuing education for directors, both formal and informal or self-directed efforts, that might include online or in-person courses, webinars, podcasts, and books that offer a general introduction to AI, tips for generative AI prompting, and/or industry-specific resources; ideally directors will be introduced to new educational offerings at least every 6 months to keep current 
• Recruiting new directors with strong exposure to AI and technology oversight from current or very recent operating roles; this is currently most common for technology companies, while some other boards are waiting to see what kind of AI expertise will be most valuable 

Best Practice: Invest in board education as a continuous process, not a one-time event. AI is evolving too quickly for directors to stay current without ongoing learning tailored to the company’s strategic context.

Most boards are adapting governance structures and policies to ensure appropriate attention to AI Oversight. Among the actions being taken: 

• Intentionally making AI Oversight a direct responsibility of the full board and ensuring that AI-related topics are a regular agenda item 
• Assigning AI Oversight to a specific committee, such as a technology committee, that can engage deeply on the topic and deliver reports and recommendations to the full board 
• Analyzing the risks and ethical implications of AI and working with management to ensure there are appropriate policies and guardrails in place.  

Best Practice: Foster a tone of responsible innovation, where the board supports experimentation while requiring accountability, transparency, and ethical discipline.