ScienceNot yet confirmed elsewhere1 publisher2 min readPublished
Only 91 of 953 AI initiatives on 15 Canadian university sites are aimed at instructors
A scan of 15 Canadian university websites found 953 public AI initiatives, 91 explicitly aimed at instructors. The authors, before peer review, describe campuses choosing different AI models as federal money and a 1 million-student literacy goal arrive.
The Scientist · Science desk
Key figures: approximately 9% of the 953 initiatives identified were explicitly instructor-facing teaching initiatives; 8 of the 15 institutions were monetizing some form of AI education; a federal AI literacy strategy commits to reaching 1 million entry-level postsecondary students.
| Figure | Value | Note | Claim |
|---|---|---|---|
| Instructor-facing initiatives, approximately | 9% | 7 | |
| Institutions monetizing AI | 8 of 15 | 8 | |
| Federal AI literacy goal | 1,000,000 students | 1 |
What happened
- The authors reviewed the 15 websites and also scraped them with search terms and keywords, and that is how the 953 items were found.
- They grouped campuses into models of response: governance and coordination, entrepreneurship, teaching-and-learning-first practice, and domain-specific AI.
- Eight of the 15 institutions were monetizing some form of AI education.
- The authors say instructors are being asked to decide when AI supports learning, when it undermines it, and how assessment should change.
Why it matters
- exposure Instructors carry the assessment and responsible-use calls, and about one in ten of the counted initiatives is aimed at them.
- decision Campuses that lean on platform access and guidelines face a choice about funding instructor support too, because the research the authors cite finds access alone does not transform an institution.
- constraint With a single scan window and no comparison group, 953 and 91 have no baseline, so neither can be called high or low.
The 953 is a count of items, and items differ in size. The authors sorted them by type: teaching and AI literacy, programs and credentials, entrepreneurship, external collaboration, infrastructure, events, funding, student groups and governance [5]. A student group and a funded infrastructure project would each be one line in that tally. The excerpt does not describe any weighting by budget, enrolment or staff time.
That bears on the instructor figure. The authors put 91 of the 953 at approximately 9% [7]; the division gives 9.5% [11]. The difference is rounding. The word "explicitly" matters more: support for instructors that is filed under another heading would not appear in the 91.
The authors treat the teaching result as a gap that deserves attention [10]. They describe a familiar institutional response, in which a university provides access to an AI platform, publishes guidelines and assumes adaptation will follow [16]. Their conclusion is that universities "may need to invest just as deliberately in the human capacity surrounding AI as in AI itself," they wrote [14].
The thing this doesn't tell you is whether any campus's mix of initiatives fits its public mission. The authors' headline poses that question. What their findings suggest, they wrote, is that "there is no single path for responding to and adopting AI" [15]. We think the instructor count is the finding worth following up. It would need budget and staff-time figures behind it before anyone calls 9.5% a shortfall.
The eight-of-15 count has a similar limit. It is 53% of the sample [12]. The authors separate AI literacy from credentialization [9], and the federal commitment is counted in entry-level students [1]. A tally of institutions cannot show how much paid AI education reaches those students.
What to watch
- Peer review of the scan, and whether the published version reports per-university counts or weights initiatives by budget or staff time.
- A repeat scan with the same method, which would give the 953 and the 91 a baseline.
- Any progress reporting on the federal commitment to 1 million entry-level students that separates AI literacy from paid credentials.
Clarity's read
What the record supports and how the coverage leans. The claims behind it follow.
Reality
- Evidence40
- Adoption35
- Hype gap+10
- Incentives
- Insufficient
- Confidence40
Claim ledger
Ranked by verification strength, evidence, and original report placement.
- [1]
The federal government is investing heavily in university-based AI research and has introduced an AI literacy strategy that includes a commitment to reaching 1 million entry-level postsecondary students.
- [2]
The authors, with Guy Levesque of the University of Calgary's Hunter Hub for Entrepreneurial Thinking, scanned publicly visible AI activity at 15 research-intensive universities in Canada between March and June 2026.
- [3]
The authors examined the 15 university websites and also scraped them using search terms and keywords, identifying 953 publicly documented AI initiatives.
- [4]
The research has yet to be peer-reviewed, and the scan is not intended to give a comprehensive picture; it is a provisional, comparative look.
- [5]
The initiatives related to teaching, student learning and AI literacy, programs and credentials, entrepreneurship, external collaboration, infrastructure, events, funding, student groups and institutional governance.
- [6]
The authors theorized institutional models for responding to AI: governance and coordination; entrepreneurship; teaching and learning-first practices; and domain-specific AI models.
- [7]
Of the 953 initiatives identified, only 91, approximately 9%, were explicitly instructor-facing teaching initiatives.
- [8]
Eight of the 15 institutions were monetizing some form of AI education.
- [9]
The authors distinguish AI literacy from credentialization; universities are developing certificates, microcredentials, degree programs and executive education related to AI.
- [10]
The authors present the teaching result as a gap that deserves attention.
- [11]
91 of 953 initiatives is about 9.5%, roughly one in ten.
- [12]
Eight of 15 institutions is about 53% of the sample.
- [13]
Research on technological change in higher education has repeatedly demonstrated that access to technology does not, on its own, transform institutions.
- [14]
The authors wrote that universities "may need to invest just as deliberately in the human capacity surrounding AI as in AI itself."
- [15]
The authors wrote that their findings suggest "there is no single path for responding to and adopting AI."
- [16]
The authors say the institutional response can easily become tool-centered: provide access to an AI platform, publish guidelines and assume adaptation will follow.
- [17]
Instructors are being asked to determine when AI supports learning, when it undermines intended learning, how assessment should change, what responsible use looks like and what students need to know before delegating tasks to AI.
Sources
1 independent publisher whose own reporting we read for this story.
- phys.orgUniversities are making different choices about AI. How will they fit with their public missions?
1 article · October 12, 2026
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