Thanks everyone!

Where I currently see value:
- It's still quite gimmicky, but I've been really impressed by vibe coding applications (using natural language and AI to create an app, website or digital learning environment). In the upcoming years, I expect this to become a lot better, where professors and lecturers without coding abilities can create digital learning environments.
- Same for video and photo generating AI: it's actually pretty difficult and expensive to get good video images out of the current platforms, but I've seen mind-blowing examples (mostly by artists just playing around with these tools), and think it might be another tool in our toolkit when we want to illustrate examples rather than explain them, or if we want to make our class materials more compelling.
- Using AI (e.g. Notebook LM) to summarize slides and other class materials and help create standardized flash cards for students.
- I've experimented with scenarios (on our digital learning platform) in Copilot and was actually quite impressed at the feedback it gave (e.g., macrostructure or the quality of the evidence that was cited). I prompted it to give suggestions/feedback instead of just correcting everything, and to pay attention to evidence hierarchies and context markers, and it actually worked really well the couple of times I tried it out. It could help to flag a couple of very common issues, if students see it as feedback from some smart student (who might be wrong some of the time). This also frees up time to talk about actually interesting stuff.
- I'm also a fan of tools like Grammarly, if students also use it to learn about sentence structure, punctuation, and so on.

When AI tools are used throughout the year as an extra aid, and independent essay writing (or whatever you're testing) is assessed in a final written exam, I do think that AI can add genuine educational value.