CLGImpactConference2026

I never planned on a career in postsecondary education. I came into it from industry, expecting to teach for a while at Bow Valley College and figured that would be that. Instead, that "for a while" turned into a career that took me through some of the most unpredictable environments in the sector: from the classroom, into organizational change at SAIT during a period reshaped by a major donor's vision for the school, and eventually to Olds College, where I found myself learning the ins and outs of an entirely new world, horses included.
 
This session is a light, honest walk through that path, and what it taught me about flexibility, learning, and resilience when nobody hands you a manual for the job you're about to do. I'll share what it was like to keep starting over in institutions that were themselves in flux, the moments I had to learn fast or fall behind, and why the skill that mattered most wasn't expertise in any one place, it was the willingness to stay a beginner again and again.

Artificial Intelligence is arriving in post-secondary institutions faster than the human systems designed to support it. Research consistently shows that equitable AI integration requires more than access to tools — it demands inclusive governance, sustained faculty and staff development, student AI literacy, transparent accountability structures, and meaningful stakeholder participation. Yet emerging Canadian evidence reveals that readiness is partial, fragmented, and uneven: personnel are often uncertain whether institution-wide policies even exist, faculty report governance and relational concerns, and marginalized student groups face persistent barriers to equitable access (Shahin, 2026; Woodworth & Ballantyne, 2025; Lin et al., 2024).
This session argues that the most strategic investment post-secondary institutions can make right now is not in AI tools — it is in the social infrastructure those tools will inherit. AI does not create equity or accountability; it reflects and amplifies whatever systems already exist. If our human systems are fragmented or unsustainable, AI will scale those gaps, not close them.
Drawing on a synthesis of over 30 peer-reviewed studies, this session introduces the RISE Framework — a practical model for building institutional social sustainability across four dimensions: Relational trust, Institutional integrity, Social equity, and Ethical readiness. Participants will leave with a concrete action plan for strengthening institutions human systems before — and alongside — AI adoption.