Canada’s new AI strategy calls for broader AI literacy, stronger public trust and responsible AI adoption, including AI learning for post-secondary students. In a Canadian university case study on AI policy in higher education co-authored with Emily Ballantyne, acting director of teaching and learning at Mount Saint Vincent University (MSVU), faculty experience with AI policy direction was examined. Faculty need practical ways to decide when AI belongs in learning, when it does not and how it changes trust, assessment and student agency. Guidance across higher education remains uneven, with comparative studies showing approaches ranging from restrictions and academic integrity rules to disclosure requirements, faculty discretion and support for responsible experimentation. Research identifies recurring gaps in policy communication, assessment guidance, professional learning and consultation with faculty. Students may encounter different expectations across courses while instructors are often left to interpret broad institutional principles. AI has changed the conditions under which trust, learning and assessment happen. Thoughtful international AI policy frameworks for education exist, although many were developed before tools such as ChatGPT became widely available. Cecilia Ka Yuk Chan, a professor of education at the University of Hong Kong, developed an AI Ecological Education Policy Framework identifying three areas (pedagogical, governance and operational). Canadian post-secondary institutions also need to include equity commitments, including responsibilities to Indigenous communities, and inequities in teaching conditions. The mixed-methods study involved 53 faculty members who completed a survey and 12 who participated in three focus groups, all full-time or part-time faculty at MSVU from varied