Educator Use of AI for the Work of Teaching
If you want to create a feisty discussion at your institution, hold a session on whether faculty can/should/could use AI to write a reference letter for a student. Or a session on whether faculty can/should/could use AI to give feedback on an assignment. Or to write a lesson plan, or respond to a student email, or prepare alternative formats for class materials, or many other use cases.
Just as there are many students using AI for learning, there are many educators using AI for the work of teaching. Some are doing so transparently, others are in the “shadow use” of AI. Some are using institutionally endorsed tools like Microsoft’s Copilot for Microsoft campuses, or institutional LLMs like the walled garden tool at UBC, others are using free tools and inputting student data.
Educators are using AI across a spectrum of teaching activities, from administrative tasks like syllabus creation and email responses to more pedagogically sensitive areas like grading rubric development and personalized learning support. Understanding this full range of applications helps institutions develop more comprehensive policies and support structures.
We know that all of these uses are taking place, and so how do we advise and what do we advocate for at our institutions?
We see AI as offering many uses beneficial to educators and the work of teaching, and recommend that teaching and learning leaders plan and offer programming and support to educators to understand how they can use AI in their teaching in responsible and beneficial ways, and in ways that align with their values as educators.
For example, AI could be seen as a partner or assistant in developing courses, assessments, or learning activities. High-benefit, lower-risk AI applications for educators include: creating diverse question banks, generating alternative explanations for complex concepts, developing scaffolded learning activities, creating visual aids and infographics, translating materials for multilingual learners, and automating routine administrative tasks. These uses can free up educator time for higher-value activities like mentoring, creative lesson design, and individualized student support.
There will necessarily be some use cases that warrant wider institutional conversation and debate – use for assessment, for instance, while some use cases like preparing multiple formats of materials to increase accessibility are less contentious.
Institutions should establish clear guidelines distinguishing between AI uses that enhance teaching effectiveness and those that might compromise educational integrity. Consider developing tiered policies that address low-stakes administrative uses differently from high-stakes assessment applications. Educator use of AI should be clearly specified in relevant course materials, syllabi and assessments.
To get you started in determining what use cases you can comfortably advocate for and how to develop programming around those uses, consider some of these resources:
- Anna Mills “Should Educators Be Using AI? Addressing Ethics as We Explore AI Assistance” (video, 1 hour, 32 minutes)
- Stephanie Verkoeyen and the AI Dialogues podcast “Instructor perspectives on the use of AI for evaluation”
- Jason D. DeHart, Suriati Abas, Raúl Alberto Mora, Damiana Gibbons Pyles (eds.) (2025) “Reimagining Literacy in the Age of AI:Theory and Practice
- Trošelj, D. B., Maričić, S., and Ćurić, A. (2024). Growing Interest in AI in Education: Systematic Literature Review.
- AI in Higher Education Resource Hub, TeachOnline
- Teaching in Higher Ed AI Resources, Teaching in Higher Ed
- Assessment and AI. Teaching Support Centre, Western University
- Ethan Mollick’s 15 Times to use AI, and 5 Not to
- Kim, Jinhee. “Leading teachers’ perspective on teacher-AI collaboration in education.” Education and Information Technologies 29.7 (2024): 8693-8724.
