Across recent research and practitioner guidance, a consistent theme emerges: AI is most productive when it automates the routine so you can focus on the human. In practical terms, AI can meaningfully reduce the time you spend on repetitive, well-defined tasks. What it cannot, and should not, replace is the relational, ethical, and judgment-driven work at the heart of teaching.
What Educators Can Productively Automate (with Oversight)
AI works best on routine tasks with clear constraints. Importantly, it should be used to create partial automation, not full automation: AI handles first drafts, structure, and/or mechanics, while you retain final judgment and accountability.
A helpful way to think about AI is as a new, overconfident graduate teaching assistant. It is fast, enthusiastic, and often surprisingly capable, but it lacks context and discernment. It needs oversight to be effective.
Lesson Planning and Instructional Preparation
Many professors report that AI is most useful during course preparation, when cognitive load is high and time is scarce. AI can support planning efficiency by helping you:
- Brainstorm and outline lesson plans
- Draft and align learning objectives
- Locate, summarize, and adapt instructional materials
- Create lecture scripts
- Generate slide structures, visuals, and examples
Used thoughtfully, these tools reduce “blank-page paralysis” and free up mental energy for higher-level instructional decisions.
Drafting Instructional and Supporting Content
AI can also generate first-pass instructional content, including:
- Introductions and summaries
- Explanatory text
- Worked examples
- Quiz questions
- Discussion prompts
- Assignment prompts
- Rubric criteria
The key here is treating AI drafts as drafts, not finished products. You remain the disciplinary expert, responsible for accuracy, tone, and alignment with learning goals. Every output should be reviewed for bias, clarity, and appropriateness.
Administrative and Logical Workflows
AI is also well-suited for automating tasks that don’t require your subject matter expertise, such as:
- Scheduling and coordination
- Accessibility fixes (captions, alt text, formatting)
- Routine communications (announcements, reminders)
- Drafting standard emails or responses
These are low-risk, high-return uses of AI that can quietly reclaim time without reshaping your pedagogy.
Practical and Responsible Implementation
AI improves productivity most when it is intentionally implemented. Here are practical guidelines for getting started:
- Start with outcomes, not tools.
Ask yourself: “What do I want students to learn? Where am I spending time that doesn’t directly support that goal”? That will help you determine where and how AI can best help. - Use AI for brainstorming and first drafts.
Let AI generate options, structures, or rough drafts. Then, apply your expertise to refine, contextualize, and improve them. - Adopt incrementally.
Start with one low-risk use case (e.g., drafting discussion questions or accessibility fixes). Early wins build confidence and reduce cognitive overload. - Redesign workflows, not just tasks.
Real productivity gains emerge when time saved is intentionally redeployed toward tasks such as feedback, mentoring, curriculum improvement, or student support. - Document your prompts and practices.
Treat effective prompts as reusable teaching assets. This reduces inconsistency and increases reliability over time. - Maintain transparency with students.
Students are often more aware of AI use than we assume. Clear communication builds trust and models ethical engagement.
Used this way, AI becomes a quiet partner in your teaching practice rather than a disruptive force. AI is neither inherently good nor inherently harmful. Its impact depends on whether it is used to hollow out teaching or to protect and amplify what makes teaching meaningful.
Used thoughtfully, AI allows you to spend less time on the mechanical work of teaching and more time on the relational, intellectual, and ethical work that only humans can do. In that sense, AI productivity is a means for better feedback, deeper mentoring, and more intentional teaching. AI adds value not by replacing professors, but by giving them more time to do the human things that make education impactful.
Sources
- Lee, D., Arnold, M., Srivastava, A., Plastow, K., Strelan, P., Ploeckl, F., Lekkas, D., & Palmer, E. (2024). The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives. Computers and Education: Artificial Intelligence, 6, Article 100221. https://doi.org/10.1016/j.caeai.2024.100221
- Lee, K. (2025, October 1). AI productivity in education: Real gains, costs, and what to do next.Swiss Institute of Artificial Intelligence. https://siai.org/memo/2025/10/202510280930
- Li Haoyang, D., & Towne, J. (2025, January 9). How AI and human teachers can collaborate to transform education. World Economic Forum. https://www.weforum.org/stories/2025/01/how-ai-and-human-teachers-can-collaborate-to-transform-education/
- Marymount University. (2024, August 15). How leaders can use AI in education. Marymount University. https://marymount.edu/blog/how-leaders-can-use-ai-in-education/
- Muncey, N. (2025, June 9). Key strategies for using AI to boost teacher productivity and reduce workload. https://schoolai.com/blog/strategies-how-to-boost-teacher-productivity-reduce-workload-with-ai
- Nagelhout, R. (2025, April 8). AI can add, not just subtract, from learning. Harvard Graduate School of Education. https://www.gse.harvard.edu/ideas/news/25/04/ai-can-add-not-just-subtract-learning
- Office of Communications, College of Education. (2024, October 24). AI in schools: Pros and cons.University of Illinois Urbana-Champaign. https://education.illinois.edu/about/news-events/news/article/2024/10/24/ai-in-schools–pros-and-cons
- Parker, J., & Barber, M. (n.d.). AI productivity tools for educators. University of Florida, Center for Teaching Excellence. https://teach.ufl.edu/resource-libraryold/ai-productivity-tools-for-educators/
- Stanford Graduate School of Education SCALE Initiative. (2025, August 14). Stanford study: Teachers lean on AI for productivity. SCALE Initiative. https://scale.stanford.edu/news/stanford-study-teachers-lean-ai-productivity
- University of North Texas, Division of Digital Strategy & Innovation, CLEAR. (n.d.). Using AI in the higher education classroom. University of North Texas. https://digitalstrategy.unt.edu/clear/teaching-resources/theory-practice/using-ai-in-higher-education-classroom.html
- S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations (Report). U.S. Department of Education. http://ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
