Why Faculty Resistance to AI Makes Sense, and What to Do About It

Faculty concerns, practical examples, and the case for thoughtful AI use in higher education

Faculty resistance to AI shows up regularly in conversations on campus. The questions are practical and understandable. Many worry about workload, whether students will cheat, and what this technology means for their role and their connection with students. One participant in the project said it directly: “I have colleagues in [my] department who also teach, and they are not fans of AI. I’ll just say it that way” (from project interviews).

These concerns have some foundation. Projections indicate real changes ahead. According to data compiled in 2025, “30% of current U.S. jobs could be automated by 2030; 60% will have tasks significantly modified by AI” (Prestianni, 2025). Faculty anxiety about replacement has some basis in reality (Selwyn, 2019).

At the same time, complete avoidance creates its own problems for students entering workplaces that already use these tools. The useful approach is careful evaluation using our own expertise rather than blanket rejection. Start with tasks that save time without changing the core of the work. One faculty member shared a clear benefit: “I’ve been using generative AI to help me write assignment instructions… Writing case studies, I can write one example, and then say, ‘Here’s the information I need this case study to include. Can you write me three more?’ Something that might take me an hour, AI can do immensely quicker. It saves a ton of work” (from project interviews).

Another participant captured the bigger picture this way: “AI isn’t going to replace people, but people who use AI will be replacing those who don’t, and I think that’s a really good thing. That’s why I get pretty squirrely in the head, I guess, when I see faculty saying, no, we’re going to resist it” (from project interviews).

The electricity comparison often comes up. We use electricity and computers every day. The real question is how we learn to work with AI in ways that help our students. Think about a colleague who feels hesitant. What seems to be driving that feeling? A short conversation about one specific task they struggle with can open the door better than any big speech about the future.