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Insights from the OnBoard Governance Council’s inaugural Q1 interview series.
A board AI strategy is a governance-level plan that defines how an organization will evaluate, adopt, and oversee artificial intelligence. In 2026, most boards still do not have one. According to OnBoard’s Governance Advisory Council — a group of six governance leaders spanning healthcare, education, cybersecurity, nonprofits, and corporate strategy — that gap is about to become expensive.
During Q1 2026, OnBoard interviewed each council member with the same set of questions: What should boards be getting ahead of this year? Where are they overconfident? What muscle should they build? AI governance dominated the conversation across every interview, but the shape of the challenge looked different depending on who was speaking.
The Three Groups That Aren't Talking
Donna Hamlin, founder and CEO of BoardWise, identified the most common structural failure. In most organizations, three groups are evaluating AI independently: the board, management, and the technical implementation team. None of them are coordinating.
“They’ve got the board looking at AI, they’ve got the management looking at it, and they’ve got the designer, but they’re not talking to each other,” Hamlin said. “And then you get a mess because they’re all looking at it differently and then they start to fight.”
Hamlin advocates for bringing all three groups together before any tools are selected or policies drafted. She calls it the “Three Musketeers” approach. “It’s a prep step that gets it smart before you start,” she said.
Data Quality Before AI Policy
Rick Doten, the Council’s cybersecurity and AI strategy expert, was emphatic about prerequisites. “The three top things for successful AI implementation are data quality, data quality, data quality,” he said.
Doten’s argument is that AI amplifies whatever it finds in your data. If your organization lacks a data governance program — data classification, retention requirements, access controls — AI will surface and scale those problems faster than any human process would. “While humans are natural to deal with uncertainty or inaccuracies in the data, AI is not,” Doten said.
Hamlin reinforced the point globally. Data sovereignty questions are intensifying in every region. Countries are building their own AI platforms because they do not trust others with their data. For boards, this means defining data ownership is no longer a technical project. It is a governance obligation.
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The Velocity Gap
Traditional board governance runs on quarterly cycles. A new initiative might take three meetings to move from concept to approval. AI does not wait for three meetings.
“The damn tools are still under construction, and they change overnight,” Hamlin said. Doten agreed, noting that AI agents — software that makes autonomous decisions — will move from 1% production adoption to widespread deployment by the end of 2026. “It is going to be the abstraction layer for how we interact with software,” Doten said.
Even boards that are not deploying AI directly face downstream exposure. Their software vendors are embedding AI whether customers ask for it or not. “Even if you like to say you don’t do AI, your affiliates and upstream third parties do, and they may be a risk into your area,” Doten said.
Not Every Board is Ready for This Conversation
AJ Crabill, who works primarily with school districts and municipal boards, offered a reality check. Many board members are not technologists and are not thinking about AI at all. “Absent somebody having that conversation with them, I think the opportunities just bypass folks just because they don’t have the expertise,” Crabill said.
Larry Tyler, a healthcare governance expert, noted that in his sector, AI is being absorbed through existing clinical platforms rather than through board-level strategy. “I don’t see the boards getting into AI at this point because Epic’s got the AI,” Tyler said.
Vernetta Walker described a gap between individual behavior and organizational policy in the nonprofit sector. Directors are already using AI privately for meeting prep and financial analysis — surveys suggest roughly 70% are — but most boards have not discussed it formally. When Walker mentioned she had used AI to analyze financial statements for a board meeting, the immediate reaction was caution, not curiosity.
Judgment Is the One Thing You Cannot Outsource
Every council member converged on a final point: AI can make governance faster, but the board’s core responsibility — judgment — is human and must stay that way.
“Artificial intelligence needs human intelligence really badly,” Hamlin said. “I see AI as a tool of ideation or suggestions, not the answer.”
Doten used the same language from his cybersecurity background: “Humans are providing the judgment. We cannot outsource that to AI.”
Crabill framed it as a resource allocation question. If AI can handle document summarization and operational catch-up, that time should be redirected toward “generative dialogue of trying to see over the horizon and of deliberation and decision making.” Those are the highest-value activities a board performs, and no AI tool can replicate them.
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What Boards Should Do Now
Based on the Council’s collective guidance, boards heading into mid-2026 should prioritize five actions:
Convene a cross-functional AI committee that includes board, management, and technology representation. Align on objectives and risk tolerance before evaluating any tools.
Conduct a data governance audit. Map what data you have, who owns it, what’s proprietary, and what rules apply. This is the prerequisite for responsible AI adoption.
Build an adaptive AI governance framework designed around foundational questions — build vs. partner, centralized vs. distributed, velocity tolerance — rather than specific tools that will change by next quarter.
Account for downstream AI exposure. Even if you are not adopting AI, your vendors and partners are. Understand where AI is already making decisions in your ecosystem.
Protect the judgment function. Use AI to reduce time on routine governance tasks. Reinvest that time in the strategic thinking and fiduciary oversight that only your board can provide.
This post draws from the OnBoard Governance Advisory Council’s inaugural Q1 2026 interview series. For the full analysis — including predictions on board assessment, strategic planning, risk oversight, and board leadership in uncertain times — see the companion white paper: 2026 Governance Predictions: What Boards Must Get Right This Year.
About The Author
- Tyler Naples is an SEO Strategist focused on building scalable organic growth systems for OnBoard, the leading board management software solution. He specializes in connecting high-intent traffic segments with content that ranks, resonates, and converts.
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