AI Resilience Report forMathematical Science Teachers, Postsecondary

Right now, AI isn't replacing math professors — it's mostly being used alongside them, especially for the tasks that surround teaching. At the University of Texas Permian Basin, professor Eric Baker built an AI Teaching Assistant using ChatGPT that lets students ask questions about course material, due dates, and grading rubrics at any time ^[1], essentially extending office hours to 2 a.m. — directly augmenting one of the most automation-prone tasks in this job. Researchers are also using AI to train future teachers: a Kennesaw State project funded by a three-year, $300,000 National Science Foundation grant created AI student-agents that simulate classroom interactions ^[2] so pre-service math teachers can practice responding to student thinking.

On the course-design side, Arizona State University quietly launched an AI course builder that pulls from faculty content ^[3], and Education Week reports the National Council of Teachers of Mathematics is urging educators to stay current with AI trends while building healthy skepticism about its limitations ^[4]. The deeper, human-centered tasks — curriculum design, committee work, mentoring — remain firmly with people.

Adoption is happening fast in some places and slowly in others. Veteran math educator Lew Ludwig writes in the Mathematical Association of America's blog that many junior faculty already use AI as a "thought partner" but do so quietly because colleagues view AI users with suspicion ^[5] — a social barrier that slows open adoption. On the other hand, the AAUP's spring 2026 Academe issue warns that administrators are signing ed-tech contracts and launching AI initiatives without consulting faculty governance, because AI offers "another seeming way to do more with less" ^[6] at underfunded institutions — a powerful economic push from the top down.

The good news for students worried about their future professors: as one Cal Poly Pomona mathematician put it, the calculator didn't replace mathematicians, and the skills that matter most — creativity, critical thinking, mentorship, and judging when AI is wrong — are exactly the ones AI is worst at. Learning to work with these tools is probably the smartest move you can make.