Hi all,
Tiffany here.
It’s Focus Friday and today we have a chance to lean into a topic that many of you have been asking about: the relationship between industry and postsecondary institutions. So, today’s session (12:30-1:30 ET) will explore that broader ecosystem, beyond just work-integrated learning, and diving into research partnerships, commercialization, applied research, talent development, and how institutions and industry are actually working together (or could be working together better).
Lindsey Fair from Invest Ottawa for this conversation. Lindsey brings a perspective that sits right at the intersection of these relationships, and I’m looking forward to digging into how this all works in practice.
As always, the format is simple: I’ll kick things off with a few questions, and then we’ll open it up for discussion. Bring your coffee, come hang out.
You can join us today here: https://us02web.zoom.us/meeting/register/CZKp1t7QR8u2yuDYw8d79Q
See you at 12:30 eastern!
Looking Back
Two weeks ago, our Focus Friday conversation turned to one of the most requested topics we’ve had: how AI is actually being used within institutions. Bringing together colleagues from across teaching and learning, IT, research, libraries, and graduate education at the University of Alberta, the session offered a rare cross-functional view of what institutional AI adoption looks like in practice and just how complex it is to coordinate.
A central theme throughout the discussion was that AI is not primarily a technology challenge, but a literacy one. Across all areas, panelists emphasized that the real work lies in developing what might be called institutional fluency: not simply how to use tools, but how to evaluate outputs, understand limitations, navigate ethical considerations, and apply and discuss AI thoughtfully within academic contexts. This reframing, away from tools and toward capability, suggests that AI literacy is quickly becoming a core academic and professional competency.
At the same time, the conversation highlighted the extent to which AI activity is unfolding across institutions in a highly decentralized way. Teaching and learning units, research offices, IT teams, and libraries are all advancing work in parallel, often with different entry points and priorities. What was particularly striking in this case was not the existence of a single centralized structure, but the degree of coordination taking place across these units as much of it is informal, relationship-driven, and evolving in real time. In many ways, the challenge is less about launching new initiatives and more about connecting the ones already underway.
The question of how to balance innovation with institutional risk also featured prominently. Rather than mandating AI adoption, the approach described focused on enabling responsible experimentation, supported by guardrails around data privacy, intellectual property, and ethical use. This reflects a broader shift toward positioning institutions as facilitators of AI engagement rather than regulators of it, while still maintaining a clear awareness of enterprise risk. Honestly, kudos to UofA on this in my opinion.
The conversation also made clear that the most significant barriers at this stage are cultural rather than technical. Faculty engagement remains uneven, with some actively experimenting and others hesitant to engage at all. Concerns around academic integrity, ethics, and even environmental impact are real and important, but in some cases are also contributing to a reluctance to fully participate in the conversation. Institutions are responding through a mix of large-scale events, targeted workshops, and discipline-specific discussions, but progress remains uneven.
These dynamics are particularly visible in the student experience. Students are navigating a landscape where expectations around AI use can vary widely from one classroom to another, leading to uncertainty about what is permitted and how they are expected to engage. The discussion underscored the importance of bringing student voices more directly into these conversations, as well as the growing recognition that some form of baseline AI literacy may eventually become a standard expectation for graduates.
Perhaps most notably, the session reinforced that this is still an emergent space. Institutions are experimenting, adapting, and learning in real time, often without clear precedents to follow. As one panelist noted, everyone is at a different point in this learning journey and part of the value of conversations like this is simply making that work more visible.
This is exactly why these sessions continue to resonate. Not because there is a single model to replicate, but because sharing how institutions are approaching these challenges helps move the conversation forward collectively.
You can find the full episode on the Higher Education Strategy Associates Youtube Channel: https://www.youtube.com/watch?v=9vMG1Cf_v3Q
And as always, if there are topics you’d like us to explore in future sessions, please send them along.
