Artificial intelligence is no longer a future concern in higher education; it’s already embedded in how institutions write, analyze, and communicate. Yet for many accreditation and assessment professionals, it still feels risky, opaque, or even incompatible with the values of peer review and institutional integrity.

This session explores how AI can be used responsibly and strategically to support accreditation work without replacing professional judgment. Drawing on real-world examples from accreditation self-studies and institutional effectiveness work, this presentation will demonstrate how AI can assist with synthesizing evidence, identifying gaps, aligning narratives to standards, and improving clarity—while keeping decision-making firmly in human hands.

Participants will leave with:

•    A practical framework for determining when AI is (and is not) appropriate in accreditation work.
•    Examples of AI-supported accreditation narratives.
•    Strategies for increasing campus-wide understanding of accreditation through AI-assisted communication.
•    Language to help demystify AI use for accreditors, faculty, and staff.

This session is designed for anyone who wants to use AI thoughtfully—not blindly—in support of accreditation quality and transparency.