#future-thinking

Someone called me visionary in a meeting recently. I said thank you, the way you do, before realising it was a polite way of parking my ideas. The praise felt complicated. It was like being handed a description of myself that I recognised, yet I couldn't quite shake the sense that it doubled as something less flattering: a polite way of saying my input didn't need dealing with just yet.

We don't reason our way into new behaviour. We act, uncertainly and messily, and then make sense of it by telling a story about what happened. I keep coming back to this when I watch institutions respond to AI and other challenges. Sensemaking is retrospective. Strategy is prospective. The gap between them is where people get lost.

At some point in the last two years, most universities will have convened a working group on generative AI. Some will have produced policy frameworks. Many will have run staff development sessions. A good number will have updated their academic integrity guidelines, published guidance for students, or commissioned an internal review. All of this activity is genuine, and some of it is genuinely useful.

Step into the lobby of almost any university, and you will likely find a mission statement etched onto the glass façade. It usually speaks of "excellence", "innovation", and "global citizenship". Yet, a mere few hundred metres away in a lecture hall, the reality often feels worlds apart from those lofty aspirations.

Generative AI is no longer a futuristic dream; it is here, and it is transforming higher education as we know it. From personalised learning experiences to intelligent tutoring systems, AI is revolutionising the teaching and learning landscape, presenting both opportunities and challenges. For anyone involved in higher education, understanding these changes and adapting to them is crucial.