This blog also doubles as an invitation to a national conversation we’re convening later this year. See the end for details.
There have been some quite amazing developments in AI in higher education recently. Ethiopia announced plans to open Africa’s first AI University. South Korea widened its network of universities providing “AI digital intensive programs for employees” to 38. It also announced a competition to establish 10 AI Innovation Graduate Schools. In Pakistan, the Higher Education Commission has told all universities that they need to change their curricula so that all students take one AI-related course as a condition of graduation (Kazakhstan did something similar last summer). India has taken two big steps, one to open the first-ever specifically “quantum AI” university in Andhra Pradesh and also allowed another public university to act as a full AI testbed.
And that’s just since the beginning of February.
You get a real sense, reading higher education policy in some of these countries, that AI is seen as a kind of leapfrog technology, and that by investing in this stuff massively and quickly, university systems in Asia and Africa might be able to catch up to those in the West in a single bound. I think that’s at best a partial truth, but it’s important to understand that this is how a lot of countries see the technology right now.
Meanwhile in the West, the principal stories with respect to higher education are all about how AI creates “digital idiots” and should be banned in universities (Portugal.) Big deals have been made about AI cheating in France and South Africa. The Atlantic wrote an interesting piece about how AI is overwhelming the peer review system. All of which is coming at a time when much of the West is becoming more critical of the notion of AI as a breakthrough technology. We read daily now about how AI is not actually increasing business productivity and that a majority of CEO’s report zero payoff from AI investments (though within the IT industry itself, AI does seem to be causing a pretty large reduction in headcount).
From all of this, I think we can draw two conclusions. First, obviously, the meaning and impact of AI as a set of related technologies is hugely contested. Partly, that’s because the term “AI” itself is sufficiently amorphous as to be actively inimical to mutual understanding (the likelihood that two people having a casual conversation have the same meaning of “AI” in their head, while discussing it is probably closer to zero than one), a point Karen Hao makes very well in her excellent book The Empire of AI. But partly it’s also because the impact of AI seems so disparate from one section of the economy to another. It’s a bit like when everyone got excited by MOOCs because of how good some early computer science MOOCs looked. Everyone had to pretend MOOCs were the future, but it turned out MOOCs didn’t translate easily outside computer science. One highly politicized and overfinanced sector does not make an economy.
The second, though, is that there are some geopolitical fault lines that covering global higher education when it comes to Artificial Intelligence. In developed cultures, where humanities and social sciences are (relatively speaking) more culturally dominant within universities, the focus on AI is largely about generative AI and its associated “slop”, on how using AI atrophies skills in writing and critical thinking, and on AI as a challenge to academic integrity. In Africa and Asia, where STEM subjects tend to be given greater priority (rhetorically if not financially in Africa’s case), the AI that most people are focusing on is less on the generative variety of AI, and the whole thing is being adopted with much greater enthusiasm. There is a reasonable chance that this faultline is going to turn into a chasm in the next couple of years; one result among others is that the frontier of innovation in higher education might – in this respect at least – lie for once in the Global South.
Meanwhile, over the past few weeks some very cool research being done in terms of how AI is being and should be harnessed for the improvement of higher education. For instance, the European University Association released a pretty sensible report on the use and adoption of AI in higher education. And there was a fascinating new paper (from a methodological point of view at least) about how the classroom use of AI has evolved over the last couple of years from Igor Chirikov at the Berkeley Centre for Studies in Higher Education.
If you study higher education, it’s an exciting time, maybe even (to use a decidedly overused phrase) a critical inflection point. AI companies and many of their products lack public trust and belief in their long term value, even as the underlying technology is becoming more and more impressive. The question of how to train people to develop AI is the question occupying many governments, but it’s getting people to use AI in an ethical and productive fashion which is going to be key question of the next couple of decades. And this is still very much a project in its infancy. There are no defined rules here yet, just a lot of people experimenting. What is needed are bigger, broader discussions which allow us to share experiences and collectively assess which tactics and avenues are likeliest to get us to the goal of developing imaginative, thoughtful, and evidence-based methods of training young people using Artificial Intelligence.
And that’s why we at Higher Education Strategy Associates have decided it’s time for another pan-Canadian event on the subject of Artificial Intelligence in Higher Education.
Last March, we hosted the first AI-cademy: Canada Summit for Post-Secondary Education. The conversation was urgent, exploratory, and in many ways just beginning. Now we’re coming back for the next chapter.
AI-cademy 2026 is a two-day national conference for higher education leaders advancing thoughtful, imaginative, and evidence-based AI practice. This year’s AI-cademy explores a new question: How do we make AI work for higher education in ways that are institutionally sound, ethically defensible, and strategically coherent?
We’re especially honoured to be hosting AI-cademy 2026 at the University of British Columbia on November 9th and 10th, in partnership with UBC, as part of a broader effort to bring institutional leaders together to share emerging practices, compare governance approaches, and collectively advance responsible adoption.
Canada can be a leader in Artificial Intelligence Higher Education, but only if institutions don’t try to re-invent the wheel all on their own. We can do more together than apart. We hope you’ll join us in November to be part of the scene. You can get your ticket here: aicademy.higheredstrategy.com.
