From Pilots to Practice: Scaling AI in Education with Purpose
Generative AI has had a huge impact on education. Most of the public discussion has been around what it means for assessment if ChatGPT can write an essay as well as a student. But beyond this, our universities and colleges have been fully focused on the opportunities created by AI. This goes beyond just exploring how AI can drive efficiencies—although that is clearly important—to also asking how AI can ensure the best outcomes for all students from all backgrounds, and how institutions can ensure that students have the skills they need for a rapidly changing AI-driven workplace.
AI Maturity and Adoption
It's worth reflecting on what AI adoption means. We think it’s a journey where institutions move from a stage where institutions are interested in AI and exploring its potential, towards actively experimenting and piloting. The challenge, as always, is to move beyond this and scale the use of AI. As institutions progress, and AI services becomes fully operationalised, we see staff having the skills to use every day AI tools, institutions have the right governance in place, so staff know how to use AI effectively and safely, and we see one or more processes adopting AI solutions. As we move forward AI becomes embedded within the institution. Data maturity is at such a level that it’s no longer a barrier, and AI is embedded in strategy and process. And what’s the destination? AI is supporting the delivery of learning that optimises opportunities and outcomes for all learners. The right tasks are automated, freeing staff time for creativity and human interaction.
How AI is being used in Universities and Colleges?
So where are our universities and colleges with AI? And is it having a real impact? Almost all universities and colleges are actively experimenting and piloting AI applications, and most are now well into their journey to make AI part of their everyday operations. We’ve been supporting this over the last five years through a programme of pilots, and these show the range of ways AI is being used in education. The use of AI for efficiency has been particularly successful, with tools to support everyday tasks such as lesson planning and creating teaching resources saving hours for some teaching staff. Students have been able to use AI to develop their employability skills, for example by practicing interviews in a 3D world and getting AIdriven feedback. Students have been able to use AI to create their own personalised learning resources from lecture recordings—for example, practice questions and revision notes. General-purpose chatbots can provide answers to students about all aspects of university or college life 24 hours a day.
A User-Driven Approach
One of the exciting things about generative AI is that, in many ways, its adoption has been driven by staff and students as much as by institutional strategy. It’s a technology that, at least in its basic form, is freely available to everyone. Students were early adopters, and now nearly all use it to support their studies. We’ve talked to many students to understand how they use AI. We find that they use AI to help understand complex topics, to help plan and structure their work, and to create learning resources in a format that works for them—for example, turning a research paper into a podcast. It also helps students from all backgrounds navigate academia— for example, helping them confidently write emails and understand policies.
From Experimenting to Operational AI
The challenge, of course, is to scale from these pilots so the benefits are felt across institutions. We believe that this is driven by a combination of a strategic, institutionwide approach, developing staff skills, and a governance approach that gives staff the confidence to use AI safely and responsibly. We’ve recently surveyed the university and college sector, and they are well on track. Most universities and colleges have an AI working group, have reviewed their policies, and have issued clear guidance to students. Many have now issued guidance to staff too, and most have either started or are planning institution-wide staff development sessions.
The Biggest Challenges
Perhaps the biggest challenge for the education sector is the rapid pace of AI developments at the moment. This, of course, is a fantastic thing to see, but the challenge is where to focus energy, and how to minimise the risk of investing in an approach that may rapidly become obsolete. The answer, we think, is not to lose sight of normal best practice just because the latest AI developments are new and exciting. So, let’s make sure we stay focused on the business problem we want to solve, and not on how we can use the latest shiny AI feature. For much of the education sector, efficiency is the driving concern. So, the focus should be on what is actually taking time. But we also need to ask what we are open to being AI-augmented. Education is fundamentally a human activity, and for some tasks, human contact, empathy, and understanding are the most important. Understanding whether AI can actually solve the problem should be the final stage—and for those it can’t currently, we park and review regularly, given the rapid pace of AI developments. There are, for example, many examples of processes within education that agentic AI is likely to be able to help with as the technology develops, from student enrolment to staff recruitment and finance process.
And Next?
We see no signs of a slowdown in the adoption of AI, and the next stage of focus is to ensure AI is fully embedded within an institution. So, we see a focus on data maturity, on processes to manage the full lifecycle of tools with AI, and continued alignment of strategy and AI use. Enthusiasm and energy for the thoughtful and effective adoption of AI in education shows no signs of slowing!
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Usman Ikhlaq
Usman Ikhlaq
Usman joined techUK in January 2024 as Programme Manager for Artificial Intelligence.
He leads techUK’s AI Adoption programme, supporting members of all sizes and sectors in adopting AI at scale. His work involves identifying barriers to adoption, exploring solutions, and helping to unlock AI’s transformative potential, particularly its benefits for people, the economy, society, and the planet. He is also committed to advancing the UK’s AI sector and ensuring the UK remains a global leader in AI by working closely with techUK members, the UK Government, regulators, and devolved and local authorities.
Since joining techUK, Usman has delivered a regular drumbeat of activity to engage members and advance techUK's AI programme. This has included two campaign weeks, the creation of the AI Adoption Hub (now the AI Hub), the AI Leader's Event Series, the Putting AI into Action webinar series and the Industrial AI sprint campaign.
Before joining techUK, Usman worked as a policy, regulatory and government/public affairs professional in the advertising sector. He has also worked in sales, marketing, and FinTech.
Usman holds an MSc from the London School of Economics and Political Science (LSE), a GDL and LLB from BPP Law School, and a BA from Queen Mary University of London.
When he isn’t working, Usman enjoys spending time with his family and friends. He also has a keen interest in running, reading and travelling.
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Michael Webb
Michael Webb leads Jisc’s AI team, which supports the responsible and effective adoption of artificial intelligence across the tertiary education sectors. Jisc is the UK's leading digital, data, and technology agency with a focus on tertiary education, research, and innovation. Michael has authored several recent AI reports and guides, including Jisc’s "AI in Tertiary Education" and "The Generative AI Primer". The team at Jisc provides advice and guidance, hosts community events, and runs a variety of AI pilot programs. Beyond artificial intelligence, Michael has been involved in projects surrounding the internet of things, virtual reality, and learning analytics. Before joining Jisc, he worked in the higher education sector, leading IT and learning technology services and teams.