Five Questions Boards Should Be Asking About AI in Higher Education
Move the board conversation beyond tool adoption toward institutional capability, governance, risk, investment, and strategic position.
Read briefInsights
Ideas for leaders making decisions before the answers are obvious.
Briefs, frameworks, scenarios, research, and commentary on the institutional implications of AI in higher education.
AI Readiness Is Not the Same as AI Adoption
An institution can deploy more tools and still become less capable of making sound decisions. Readiness is about the conditions for judgment and action.
Explore 3CWhat Changes When AI Becomes Infrastructure?
A framing for leaders considering the shift from individual experimentation to embedded and agentic institutional systems.
Discuss with usLeadership brief
Five questions boards should be asking.
- Which institutional decisions about AI cannot be delegated? Governance should distinguish operational choices from decisions that materially affect mission, risk, academic policy, or institutional identity.
- Where is actual practice moving faster than formal policy? Leaders need evidence about real use, not assumptions based on published guidance.
- What capabilities must the institution own? Vendor selection is not a substitute for internal judgment, literacy, data stewardship, or governance capacity.
- How will we know whether an AI investment is working? Pilots and deployments need explicit outcomes, review criteria, and a credible ability to pause or stop.
- What would we regret not preparing for now? Scenario thinking helps institutions build options before emerging technologies force decisions under pressure.