🎄 Day 20 of 25: AI governance in universities
Universities are increasingly adopting AI across teaching, research, and professional services. In 2025, effective AI governance is less about restricting innovation and more about providing clear, shared frameworks that enable responsible use at scale.
Today’s AI insight
AI governance in universities works best when it is distributed and practical, not centralised and abstract. Policies alone are insufficient; governance also includes guidance, oversight processes, risk assessment, training, and clear accountability for decisions made with or by AI.
Because universities host diverse activities — from experimental research to student assessment and administrative decision-making — governance must be context-sensitive, allowing flexibility while maintaining common principles around transparency, fairness, and human oversight.
Why this matters
Without coherent governance, AI adoption can become fragmented: different teams use tools inconsistently, risks are assessed unevenly, and staff and students are left uncertain about what is permitted or supported.
Overly restrictive governance, however, can stifle legitimate research and teaching innovation. The challenge is to create structures that manage risk without freezing experimentation, particularly in fast-moving AI landscapes.
A simple example
A university might establish:
- Clear principles for acceptable AI use across teaching, research, and operations
- Light-touch review processes for high-risk applications
- Named roles or committees responsible for oversight and escalation
- Training resources that help staff and students apply guidance in practice
This allows everyday, low-risk uses to proceed smoothly, while ensuring that high-impact systems receive appropriate scrutiny.
Try this today
✅ Review existing AI guidance and identify where it is unclear, outdated, or hard to apply in real workflows.
✅ Map where AI is already being used informally across your unit or department — governance often lags behind practice.
✅ Ensure there is a visible route for advice, approval, and challenge when AI use raises ethical, legal, or academic concerns.
Reflection
Good AI governance in universities is not about control for its own sake. It is about enabling trustworthy, transparent, and accountable use of AI, while preserving academic freedom and supporting innovation. When governance is designed as an enabler rather than a barrier, AI becomes easier — not harder — to use responsibly.