AI use cases are not an AI strategy

Universities are rapidly accumulating AI use cases.

Some emerge from faculty experimentation. Others come from administrative functions, technology teams, vendors or senior leadership.

But a collection of use cases is not an AI strategy.

A strategy requires an institution to decide where AI matters most, which outcomes it is trying to improve, what capabilities it needs, and what it will not prioritise.

Strategy requires choices

Almost every university function can identify plausible AI opportunities, but institutions have finite management attention, technology capacity and organisational readiness.

Strategy therefore requires choices about what to pursue now, what to experiment with, what to defer and what not to pursue at all.

Those choices must also reflect what implementation will require: data, integration, process redesign, governance, skills and clear ownership.

For example, a university may identify promising AI opportunities in admissions, student support and career services. But if all three depend on fragmented student data across multiple systems, the first priority may not be any one of those use cases.

It may be to create the integrated data foundation on which all three depend.

That foundation is not an AI use case in itself. But it may be the most important AI-related investment the institution makes first, because without it, several higher-value AI use cases may remain difficult to implement or scale.

A useful AI strategy should answer a few clear questions

Institutional leaders should be able to answer:

Which outcomes are we trying to improve?

Where can AI make a material difference to those outcomes?

Which opportunities are our current priorities?

What capabilities must we build to support them?

How will we know whether they are working?

And perhaps most importantly:

What are we choosing not to pursue for now?

If those answers are unclear, the institution may have substantial AI activity, but it probably does not yet have an AI strategy.

AI strategy is not a catalogue of use cases. It is a set of institutional choices about where AI deserves attention, investment and change.