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Clarify Expectations Early. Whether you embrace, permit, discourage, or prohibit the use of generative AI in your course, it’s essential to clearly define those boundaries in your syllabus and class discussions. Share your rationale with students—how your policy supports the learning goals of the course—and create space for dialogue. This transparency helps students understand not just what is allowed, but why.

Reference the AI Assessment Scale (AIAS). The AIAS helps faculty categorize assignments based on acceptable levels of AI use, from no AI involvement (Level 1) to full AI collaboration (Level 5). helps set shared expectations and can reduce ambiguity or misuse.

Sample Policies from Other Faculty. includes AI classroom policies from educators across the country. Use these examples as inspiration when drafting your own.

Design for Process, Not Just Product. Assignments that include brainstorming, drafts, revision, and reflection are less likely to be fully outsourced to AI tools. They also help students develop metacognition and higher-order thinking skills.

Personalize and Localize. Create prompts that draw on lived experiences, local issues, or current events—areas where AI tools may be less effective or out of date. These types of assignments are more resistant to misuse and more meaningful to students.

Intentionally Integrate AI. Consider giving students opportunities to work with AI tools in structured and purposeful ways. For example, you might ask AI to generate an argument and then have students write counterarguments, or use AI to brainstorm research topics or create outlines that students later critique or refine. Some faculty ask students to compare AI-generated writing to human-authored texts, or to submit annotated drafts that explain where and how AI tools were used. These types of assignments help students develop critical AI literacy while producing original, thoughtful work.

Rethink What Mastery Looks Like. With AI tools increasingly accessible, faculty have an opportunity to reassess how learning is demonstrated. Consider whether your assessments focus more on recall or reasoning, more on deliverables or developmental learning.

Emphasize Iteration. Breaking assessments into stages—proposals, drafts, peer reviews—helps emphasize student process. It also gives you better visibility into their learning and reduces the incentive to rely heavily on AI.

Support Multiple Modalities. Assessments don’t need to be papers. Encourage students to demonstrate their learning through multimedia, presentations, portfolios, or real-world applications like PSAs or client briefs. These formats often require skills AI can’t replicate and result in work that students are proud to share beyond the classroom.