AI is being used across a growing range of teaching activities, from course design to assessment and feedback. Yet faculty are starting from different points, and institutions are still working out which uses create real educational value and which introduce new risks.

Scaffolding AI in Teaching: A Practical Guide to Advancing and Evaluating AI Use in Teaching offers a structured way to navigate this landscape. It maps where AI can be applied across teaching, identifies entry points for faculty at different levels of readiness and shows how practice can progress over time.

Developed by the DEC 2026 Teaching with AI Working Group with 45 education leaders worldwide, the report provides three practical resources:

• A Teaching with AI Taxonomy Framework that maps AI use across seven domains and four levels, from Entry-Level to Expert
• An evaluation framework built around Impact, Risk and Resources to help prioritise use cases
• A Use Case Bank with real-world institutional examples to guide implementation

The report helps educators and institutions advance AI use in teaching in line with faculty readiness, while keeping the focus on meaningful learning.