However, there is another risk that receives less attention. What happens if other institutions adopt AI effectively while yours does not?
They may be those with leaders who understand the implications well enough to guide their institutions through change while maintaining trust and accountability.
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AI, by contrast, continues to advance at a pace that can make long-term planning difficult.
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A question
If you are a university leader, what is the single most important thing you believe leaders need to understand about AI?
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You can read more about the topic discussed here in my newsletter: buff.ly/kMzXWiN
However, they do need enough knowledge to ask informed questions, recognise opportunities, understand risks and make sound strategic decisions.
Leadership therefore requires balancing both forms of risk: the risk of adopting AI and the risk of failing to do so.
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It is not just a technology issue
Perhaps the biggest mistake is to view AI as a technology project.
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I raises questions about governance, workforce development, organisational culture, data management and institutional strategy. The universities that navigate AI successfully may not be those with the most advanced technology.
The risk of standing still
Much of the discussion around AI focuses on the risks of adoption. Concerns about privacy, bias, misinformation, intellectual property and academic integrity are all valid, and deserve careful consideration.
Universities that successfully integrate AI may improve student support, reduce administrative burdens, enhance research productivity and operate more efficiently. Institutions that delay engagement may find themselves at a competitive disadvantage.
The challenge is that AI is evolving much faster than most universities are accustomed to dealing with. Institutions often have planning cycles that span several years, supported by governance and approval processes that are necessarily deliberate.