Riding the AI Wave: Opportunities and Responsibilities for Educational Institutions

Richard Walker, Associate Director (Digital Education), University of York

Richard Walker, Associate Director (Digital Education), University of York

The most recent Higher Education Policy Institute (HEPI) report on Generative AI adoption by students makes for stark reading: 95 percent of students are using AI tools and 94 percent are relying on them for assessed tasks. Whether we like it or not, students are accessing AI tools on their own initiative in their study programmes and often they are going outside the ‘walled garden’ and using external tools to do so. This requires a response from educational institutions in terms of the digital toolsets that we recommend to our learners to use and the appropriate training, policy and guidance that we want them to follow.

The time for waiting for the right conditions to introduce AI services is over-institutions need to act now. And this is a message that we are hearing more frequently and from a number of different sources, not least the UK government. Note the recent government announcement by Liz Kendall (Secretary of State for Science, Innovation and Technology) in January 2026, emphasising the need for every adult in the UK to gain practical AI skills for work, with a commitment to deliver training on key skills in partnership with industry by 2030.

“Big Tech firms like Microsoft, Amazon and Google Education offer educational institutions a fast-track route to the adoption of AI services, for those that can afford it.”

Recent UCISA research indicates that UK higher education (HE) institutions are struggling to keep up with the pace of change. Formal leadership on AI developments is still evolving as institutions come to terms with the challenges and opportunities that AI presents to teaching and business processes. In some cases, staff are still waiting for a lead from senior managers on how institutions will embrace AI for teaching, learning and assessment. Main drivers from the top appear to focus on business efficiencies and cost savings, addressing the financial challenges that institutions are facing. Surprisingly, there appears to be less emphasis on the contribution that AI tools can make to improving educational outcomes. What is needed is a governance framework that enables staff and students to harness their own creativity in the use of AI tools and to do so in a controlled and responsible way, supporting enhanced learning experiences. This should be achieved by drawing on a shared set of services for staff and students, with attention to inclusion and equity for all. A level playing field is essential here, so that educational benefits from the use of AI tools are not restricted to those with the ability to pay for premium licences.

But how can this all be achieved? Liz Kendall’s announcement called for a partnership between public bodies and industry to deliver change. The Oxford Education model represents one example of how this can work. The collaboration between Google Education and Oxford University provides staff and students with access to generative AI tools such as Gemini, NotebookLM and to the accompanying Google training, supporting the integration of artificial intelligence in research and education across the university.

Big Tech firms like Microsoft, Amazon and Google Education offer educational institutions a fast-track route to the adoption of AI services, for those that can afford it. But this approach is not for everyone. The importance of digital sovereignty and independence from Big Tech has led to a pushback by some UK HE institutions, with a focus instead on local resources and infrastructure and the value of the open-source community as the way forward.

Whichever approach is adopted, it is important to up the ante with staff and student training and go beyond awareness raising and entry level AI skills development, which seems to be the level we are currently at across the UK HE sectors. The emergence of agentic AI now directly challenges the way traditional teaching and learning activities are delivered and requires a fundamental rethinking of digital learning design. The recent glimpse we saw of Einstein AI, an application designed to log into a learning management system and submit assignments, watch lecture recordings and complete discussion activities on behalf of a student prepared to hand over log on credentials, neatly illustrates this point. Applications such as this represent a wake-up call for academics who design traditional content-heavy, test-based courses, which can be completed with ease using AI tools. Indeed, they demand a new learning design approach, which prioritises learner-centred activity based on critical reflection and decision making, rather than factual recall and surface-level learning. Arguably, this is what we should be doing with learning design in any case-engaging our learners in meaningful activities which require them to be ‘present’, making connections to prior knowledge and experience.

In summary, rather than see AI developments as a threat to existing practices, I would argue that a positive frame of reference is needed to engage with the change that is coming with the AI wave, and this would serve us better in the long run. AI represents an opportunity for a re-set on course design, assessment and academic and digital skills development, rather than a return to invigilated and locked down learning environments and exam centres. The next generation agentic AI applications will drive thinking on adaptive learning and personalised learning pathways, bringing us closer to the delivery of the flexible learning experience that we have been promising our students for so long. Will this finally usher in big changes in course design, enabling flexible learning design across higher education institutions? Hopefully this will deliver positive changes that will take us in that direction.

AI

Microsoft

Financial

Learning Management

Test