Our AI survey shows the impact of strong board oversight
AI governance is not a compliance exercise; it is a primary driver of enterprise value creation and enterprise risk management. Boards that apply basic AI governance principles can help their organizations integrate AI faster, innovate better and deliver products and services with higher quality.
But most boards are falling short of these basic responsibilities, according to Grant Thornton’s 2026 AI Impact Survey.
In our survey analysis, we defined organizations with strong AI oversight as those with boards that:
- Participated in briefings or education sessions on AI;
- Established expectations around AI policies or governance; and
- Integrated AI risk and opportunity into ongoing board or committee oversight.
Although these seem like basic board duties, just 11% of the 950 business leaders who participated in the survey said their boards have done all three. The survey data shows what those 11% are accomplishing, and what the others are missing.
Organizations with strong oversight are:
- Twice as likely to have fully integrated AI into their operations compared with the entire sample (28% to 14%), and
- Almost three times as likely to have fully integrated agentic AI (26% to 9%).
These organizations are more confident in their controls, and they are four times as likely to say their AI initiatives are not underperforming.
“These companies are most likely treating AI as a category of enterprise risk, rather than a technology initiative,” said Grant Thornton Risk Advisory Services Partner Johnny Lee. “They’re establishing a multidisciplinary team to lead implementation and governance efforts, and they’re implementing control activities that prevent foreseeable risk, monitoring for risks they cannot prevent, and insuring for risks they can neither prevent nor detect.”
Boards need to ask management who is represented in that multidisciplinary team (and, if it doesn’t exist, ask why). Above all, it’s important to make sure any one functional area (such as IT) isn’t flying solo on AI implementation. Our main survey report shows a misalignment between CIOs/CTOs and COOs on AI governance needs and workforce readiness. The findings reveal that a siloed approach to AI, informed singularly by an IT perspective, will not meet the needs of the people in operations, finance, HR and legal who consume that technology.
This misalignment threatens to undermine the benefits that can be achieved with AI. But proactive boards can help their organizations navigate a path to substantial AI benefits.
Accelerating innovation and improving quality
Strong board oversight gives organizations the structure and discipline to deliver AI innovation and use AI to improve the quality of their products and services.
Fifty-nine percent of organizations with strong board oversight reported that AI is accelerating innovation, compared with just 31% of the full response population. And by a 53%-to-43% margin, those with proactive boards were more likely to say AI is helping them deliver higher-quality outputs.
Established AI governance expectations from the board boost innovation by establishing a framework for AI dialogue, safe experimentation and deployment. Board-led dialogue around acceptable risk, data use and model transparency translates into meaningful governance milestones that allow teams to stop guessing what’s permissible, to quickly create prototypes, and to focus on scaling the ones that work while abandoning the ones that don’t.
Board-confirmed AI policies also help innovation align better with strategy from the start, preventing teams from wasting time on pilots that would be doomed at later stages of development.
Meanwhile, clear expectations for AI foster discipline in product and service development that, in turn, leads to higher-quality outputs. Teams with established AI policies and governance expectations build systems meeting established standards that include:
- More rigorous data quality checks
- Better model validation and monitoring
- Documented decision-making processes
In their ongoing oversight role, boards need to make sure management is meeting its obligations by asking:
- How is the company promoting data readiness, hygiene and security?
- Has a secure, controlled environment been established for AI experimentation to protect data and intellectual property?
- What is leadership’s approach to change management — and does that contemplate clear communication with employees and partners?
- How are employees being trained to use AI?
- How are leaders preparing themselves to spearhead the effort?
“That’s half of it,” Lee said. “The other half is proactively monitoring that we’re not drifting from those lofty aspirations on the implementation side.”
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Finding solutions to skills gaps
Our survey paints a nuanced picture of strong board AI oversight’s effect on the workforce. Twenty-seven percent of organizations with strong board AI leadership say their workforce is fully ready to adopt AI, compared with just 12% of the full population.
But this optimism masks deep challenges. By a margin of 60% to 36%, organizations with strong board oversight were more likely to say talent or upskilling gaps are preventing AI from scaling impactfully. Meanwhile, 40% in the proactive board group said insufficient training has caused AI underperformance or failure, compared with 31% overall.
A deeper analysis shows that when respondents to the “preventing impactful scaling” question were permitted to select three answers, strong-board organizations were less likely to say their barriers were:
- Lack of AI governance or responsible-use standards (5% compared with 21% for the full sample)
- Regulatory or compliance uncertainty (33% vs. 51%)
- Poor data quality or data integration challenges (8% vs. 31%)
This shows that organizations with AI-focused boards have embraced the foundational AI challenges related to governance, compliance and data. This embrace allowed them to pivot to a more advanced and complicated step in AI adoption — enabling the workforce.
Workforce adoption requires strategic depth from management. It’s not enough to provide a vision, an enterprise license and a mandate that employees should just figure out the rest on their own. Returns on AI investment require leadership to:
- Redesign processes to enable AI-powered improvements
- Provide role-specific training that helps employees implement AI in their everyday work
This approach helps organizations solve one of the biggest challenges around — attracting and retaining top talent. Leaders who skillfully adopt AI will successfully recruit and retain these individuals. At the same time, boards should ensure that the flip side of the AI workforce coin is being managed, as AI introduces workforce disruption and creates a fear of job loss.
Lee said directors should be asking management:
- How are they addressing workforce disruption? Is AI deployment in a specific area being used to identity headcount reductions?
- How have they communicated to employees that they are not being asked to train tools that will take their jobs?
“A director should hear good answers to those questions before he or she feels confident that management has a handle on AI as a strategic accelerator, a worthwhile investment of resources, and a workforce-disruption phenomenon that is being well-managed,” Lee said.
Building confidence and improving performance
Leaders whose boards exhibit strong AI oversight have a substantial advantage over their peers in confidence and performance.
Just 22% of overall respondents were very confident that their organizations could pass an independent audit of AI governance and controls. Organizations with AI-focused boards scored significantly better on this metric, with 37% saying they were very confident. Although there’s still room for improvement, this finding shows that active board oversight helps organizations adopt AI that’s explainable, measurable and defensible.
The performance edge these organizations hold was even more striking. Asked to identify reasons that AI was underperforming, 34% of organizations with strong board governance said their AI wasn’t underperforming at all. A mere 8% of the total population said their AI wasn’t underperforming.
This shows that organizations whose boards establish strong AI governance eliminate chaos, reduce rework and channel creativity into areas where the organization can take advantage of the right opportunities and outflank their competitors. These organizations:
- Have well-governed data that provides AI with the raw material it needs to make a maximum impact,
- Enable cross-functional collaboration and prevent siloed duplication of efforts, and
- Develop trust that engenders confidence in AI-assisted outcomes.
It’s worth noting that while a discrete, widely accepted standard doesn’t exist yet for an independent audit of AI governance and controls, Lee believes it’s only a matter of time — and there are plenty of frameworks that provide the roadmaps for such reviews. With that in mind, boards should insist that leadership create the strong controls, documentation and audit trails that would be needed to pass such an audit.
“Even if there’s no such audit today, boards should ask management if they could pass one,” Lee said. “If you want your AI projects to succeed, you need to put a strong focus on governance — with some pressure testing from an arm’s-length assessor of some kind, whether that’s Internal Audit or an external party.”
Key takeaways
At this make-or-break time across industries, boards that lean into AI governance can set the foundation for their organizations to outmaneuver their competition. To get an edge, boards need to:
- Require formal AI capability briefings at least annually. Directors don’t need a computer science degree or coding experience. They need to understand AI’s capabilities and how these capabilities can best be applied to their organization’s strategy — and most importantly, what governance is needed to accomplish this safely and effectively. The National Association of Corporate Directors has courses and programs that can help.
- Establish policies and governance expectations, right-sized for their specific business. AI needs to align with organizational goals and values. Boards need to make sure management creates and maintains policies that balance innovation with accountability and that promote ethical, people-centric principles and compliance with emerging regulations and security/privacy best practices.
- Institutionalize AI oversight as a standing board agenda item with defined KPIs. AI risk and opportunity should always be on the calendar for the full board — and perhaps for a board committee as well. This is the only way to ensure that established policies and governance expectations are being followed. And it establishes a regular cadence for board consideration of emerging issues related to a technology that’s rapidly changing within the business environment.
A board that follows these basic principles can help an organization implement AI faster, thereby achieving benefits without taking unnecessary risks.
For more information on how to drive AI performance and how governance enables AI benefits, visit the Artificial Intelligence page on our website.
Contact:
Partner, Risk Advisory Services
Grant Thornton Advisors LLC
Johnny Lee is a Partner in the Forensic Advisory practice and the National Practice Leader of the Forensic Technology practice.
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