Institutional Policies on Artificial Intelligence in Higher Education: Frameworks and Best Practices for Faculty
Lauren Azevedo, Pedro Robles, Eric Best, Daniel J. Mallinson
Abstract
ABSTRACT This article explores institutional policies on artificial intelligence (AI) in higher education. As AI tools become increasingly utilized in academia—from research and teaching to assessment and student support—institutions face growing pressure to establish clear, ethical, and practical guidelines to help guide faculty. We examine existing institutional responses to AI adoption, identify common policies, and highlight the growing pressure that exists between innovation, academic integrity, and equitable access. Drawing on three institutional examples and current policy models, an approach to developing faculty‐focused AI policies that promotes transparency, safeguards academic standards, and fosters responsible AI use is proposed. Recommendations are made for policy development that align with institutional missions, faculty autonomy, and the evolving landscape of higher education.