A single course policy often has to cover very different kinds of work: reading notes, exams, discussion posts, essays, research proposals, presentations, and revision exercises. One blanket rule can make those differences harder to see.
The AI integration ladder treats AI use as a set of levels. Each assignment can name the level that fits its learning goal, while still leaving room for instructors to adapt the labels.
The ladder gives instructors and students a shared vocabulary for AI use across a course. The exact labels can change, but the basic idea is to distinguish between tasks where AI might undermine the learning goal and tasks where AI is part of the learning goal.
Possible policy language
AI use in this course varies by assignment. Each assignment will identify one of the following levels:
Level 0: No AI. Complete the work without AI assistance because the assignment is designed to assess your own memory, reading, drafting, or analysis.
Level 1: AI for support. You may use AI for brainstorming, outlining, vocabulary help, or revision suggestions, but the core claims, evidence, and structure must be your own.
Level 2: AI as collaborator. You may use AI more substantially, but you must document how it shaped the work and explain what you accepted, rejected, or changed.
Level 3: AI as object of critique. You will use AI in order to analyze its output, limits, assumptions, errors, or interpretive habits.
Level 4: AI as workflow tool. AI use is expected because the assignment asks you to test a research, writing, coding, or media workflow that would be difficult to complete manually.
This framework helps avoid the false clarity of “AI allowed” or “AI banned.” Students learn that tools have different consequences depending on the learning situation. AI brainstorming before a thesis workshop is not the same thing as AI-written close reading. AI-assisted transcription for a research workflow is not the same thing as AI-generated reflection after not doing the reading.
The ladder also helps instructors be more precise. Instead of writing a syllabus policy that tries to anticipate every case, the course can establish the vocabulary once and then apply it assignment by assignment.
The ladder needs assignment labels
This framework only works if assignments actually name their AI level. If the syllabus introduces the ladder but individual assignments never use it, students are left guessing where each task belongs.
The hardest level is usually Level 1. “AI for support” sounds intuitive, but students may not know where support ends and substitution begins. It helps to give examples: asking AI to suggest possible counterarguments is support; submitting an AI-generated interpretation as your own close reading is substitution.
I would ask students to classify two or three sample uses of AI during the first week of class. That turns the policy into a discussion about learning goals rather than a rule they skim once. I would also keep the ladder short enough to remember. More than five levels starts to feel like a compliance taxonomy rather than a teaching tool.