Every university leader I speak to is thinking about AI.
That is not the problem.
The problem is that ambition is moving faster than readiness. The data shows that students are already using these generative AI tools at scale, faculty are experimenting, and leadership teams are paying attention, but in most institutions the systems and governance needed to make AI useful, safe and measurable are still catching up.
This gap is what makes the new IREX and Development Gateway report so timely. From Ambition to Adoption: Insights into University AI Readiness from Around the World, authored by Razan Elayan, Mariam Ibrahim, Cameron Mirza and Tom Orrell draws on 76 respondents across 46 institutions in 25 countries, with most based in Africa and the Middle East. The findings are direct. Only 34% of respondents said their institution has a clear AI strategy linked to academic and operational priorities, fewer than 40% reported approved AI policies, and just under a fifth reported governed AI pilots that had actually made it into how the institution works.
In my own work across Africa, the Middle East and Southeast Asia, I see this tension constantly. Institutions know AI is reshaping teaching, assessment, operations and employability, and many are not waiting passively. They are setting up committees, testing tools, and backing pockets of innovation. However the distance between “we need to do something with AI” and “we have the institutional capacity to do this well” is still wide, and it’s widening.
The common mistake is to treat AI readiness as a procurement question. A platform still matters. For many institutions it will be part of the infrastructure that moves them from scattered experimentation to scaled and tested practice. Yet a platform only creates value when it is connected to the operating model around it. It has to support a strategy, help build staff and student capability, make learning more personalised and more aligned to workforce outcomes, and help the institution understand what is actually working rather than just adding another layer of digital activity.
Closing the gap takes capacity in several connected areas: faster and more effective ways to create high-quality learning content, structured pathways linked to labour market needs, clearer routes between study, skills and work experience, and data that shows whether students are progressing in the ways an institution intends.
This is increasingly where my work at FutureLearn sits. The conversations I’m having with universities are less about “using AI” in the broad sense and more about how AI-enabled learning, content creation, skills development, personal growth, employability pathways and institutional insight can hold together as one coherent student experience. The point is not more digital provision. It’s the capability to respond faster, support students better, and make clearer decisions about what improves learning and employment outcomes.
The stakes are not theoretical. Students are already using AI to study, write, research, revise and prepare for work, while the labour market they are entering changes around them. Oxford Economics research cited in the report points to rising unemployment pressure among new labour market entrants, with signs that entry-level roles are being displaced by AI at higher rates than others. When universities delay this work, the consequences show up in the experience of graduates trying to enter a market where expectations are shifting faster than many degree programmes.
Of course, no institution has all of this figured out, and they don’t need to. What the next phase needs is more honesty about the distance between AI activity and AI readiness. The appetite is clearly there. What has to come with it now is a stronger focus on institutional coordination and coherence: pulling the scattered pilots, policies and pockets of enthusiasm into something that actually holds together.
The reality of any AI conversation is that the technology will keep moving, and what matters is whether an institution can keep moving with it. The universities that take that seriously now, who have future-facing leadership, and who put the right partners and infrastructure around the ambition, will be far better placed for whatever comes next, and so will their students.
Hemani Naran is the International Development Manager – UAE at FutureLearn.
