Leadership
AI: Is It Safe?
Boards are grappling not only with how their companies deploy and govern the technology, but how it affects their own usage.
January 21, 2026
Three Top AI Concerns for Boards
Pop quiz: You’re a board director and you’ve just been given your pre-read material for an upcoming meeting. You’re pressed for time, but you’ve also been wanting to dive deeper into understanding market competition regarding a certain part of your supply chain. You:
A) Read the material in full and make notes in the margin to ask supply-chain questions at the meeting.
B) Put the pre-read into your company AI program and ask for a summary.
C) Do B and go a step further by using an outside AI program to learn more about the specific supply-chain market competition.
If you’re not sure which answer is correct, you’re not alone. As the wild west days of AI continue, employees aren’t the only ones trying to figure out how to use AI safely and productively. “The days of AI as an individual use case are over,” says Bryan Ackermann, Korn Ferry’s head of AI Strategy & Transformation. Adds Anthony Goodman, leader of Korn Ferry’s North American Board Effectiveness practice: “Today’s directors need to start wrapping their heads around this shift.”
While nearly 90% of organizations are using AI in at least one business area, only 35% of directors say their boards are using AI in their oversight roles. That’s expected to ramp up in the next year, so we asked experts about three leading areas in which directors should be mindful of AI use. Here’s what they said.
1 Governance
One of the biggest discussions playing out in boardrooms is who owns a company’s AI strategy and how to establish accountability standards. Though corporate AI experimentation is flourishing, less than 40% of Fortune 100 companies disclosed any form of board oversight over the technology as of 2024.
Experts say good AI governance starts with companies understanding how the tech fits into their strategy. Once that’s established, boards can figure out how to best understand the risks and opportunities, considering everything from company-wide AI ethics statements to what the board needs to review in full versus what committees should handle. “We’re going to see the next generation of team dynamics play out,” Ackermann says.
It’s also critical for directors to consider their own fiduciary duty; is it to use every analytical tool available to them or to only review what company management has curated for them? “Directors need support and education on how to leverage AI to be more effective in their roles,” Goodman says.
2 Auditing
Perhaps one of the most interesting AI use cases for boards involves external auditors using the tech to analyze financial statements, automate tasks, and aid in risk detection. While AI auditing tools could look particularly appealing to boards because they can significantly bring down the cost of tedious auditing tasks (hello, billable hours) and speed up the work, directors must establish clear protocols for AI use—both for employees and third parties like legal advisors and auditors. “Anything that drives performance or creates risk should pass through the audit committee,” says Jason Waterman, senior client partner in Korn Ferry’s Global Financial Officers Practice.
Board audit committees should ask their auditors how they’re using AI and work with them to establish protocols to ensure company AI oversight meshes with external auditing practices. There may also be an opportunity to negotiate contract terms to ensure certain levels of human supervision. After all, anything with a solid audit trail needs to be treated with caution.
3 AI Spending
Directors may face their biggest AI challenge when it comes to differentiating between actual value creation and experimentation—a distinction that’s becoming even more complex given the advent of agentic AI. “There’s a lot of risk associated with thinking AI is a panacea,” says Stu Crandell, senior client partner in Korn Ferry’s Board and CEO Services practice. “That’s how companies overspend.”
While global AI spending could push past $2 trillion this year, a study from MIT shows 95% of AI projects haven’t led to positive returns. And a recent Korn Ferry survey of 250 CEO and board members found only 8% are certain about AI’s return on investment.
Experts say boards should be particularly critical of AI investments driven by competitive pressure, rather than clear business cases. “To what extent does AI compromise our competitive advantage if everyone has access to the same innovation?” Crandell asks.
To help sift through these issues, boards need to understand how ROI is being measured across various initiatives and what happens when AI projects don’t deliver expected returns. There’s also a critical need for boards to understand what counts as AI experimentation versus actual business implementation. “There’s been enormous pressure on leaders to bring AI efficiencies in two to three years,” Ackermann says. “But that’s been elusive.”
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