Building an Equitable, AI Ready Campus-Technology Ecosystem: some reflections
By Professor Sam Elkington
Professor of Learning and Teaching at Teesside University, UK
This reflection follows the first session in Adobe’s “Generation AI: Empowering Creativity & Productivity Across Higher Education” webinar series.
Moderator: Professor Sam Elkington.
Speakers: Professor Chie Adachi (Queen Mary University of London) and Professor Simon Thomson (Cardiff University).
The first webinar in the “Generation AI: Empowering Creativity & Productivity Across Higher Education” series explored a pressing question: how can universities adopt creativity, productivity, and AI tools in ways that genuinely advance equity, access, and success for all? The challenge is a timely one with AI rapidly becoming embedded in workplaces, professional practice, and everyday life. The question facing universities is no longer whether AI will influence higher education, but whether institutions can create digital ecosystems that ensure all learners and staff can participate meaningfully in an AI-enabled future. Indeed, there is a clear risk that without intentional strategies, universities may inadvertently widen existing inequalities while simultaneously struggling to prepare graduates for an increasingly AI-mediated world.
To explore these issues, the webinar brought together two highly respected leaders in digital education. Professor Chie Adachi, Dean of Digital Education and Academic Director of the Centre for Education at Queen Mary University of London, shared insights from leading institution-wide AI strategy within one of the UK's most diverse universities. Professor Simon Thomson, Director of Flexible and Lifelong Learning at Cardiff University, brought extensive experience from both Cardiff and his previous work at the University of Manchester, where large-scale institutional AI initiatives have been developed and implemented. Together, they offered a refreshingly honest account of both the opportunities and complexities associated with creating an equitable AI-ready campus with several recurring themes emerging.
AI is a Wicked Problem – we should respond accordingly
One of the most powerful themes emerging from the discussion was the recognition that an AI-ready institution needs to move beyond simple technological solutions towards institution-wide cultural, pedagogical, and organisational change. Professor Adachi described AI in higher education as a "wicked problem", characterised by competing priorities, uncertainty, and constantly evolving technologies. This framing matters. Too often institutional conversations focus narrowly on selecting tools and/or creating policies. Instead, both speakers argued that AI adoption requires universities to grapple simultaneously with educational, ethical, financial, environmental, and societal considerations. Significantly, both speakers cautioned against technological solutionism, the belief that new technologies automatically solve existing educational challenges. Every technological innovation creates new opportunities, but also new risks and responsibilities which need to be considered with equal care and attention.
Equity Beyond Access and adoption
While discussions about AI often centre on access to tools, both speakers argued that equity extends far beyond technology provision. Professor Adachi highlighted the emergence of a "shadow AI university", where students with the confidence, resources, and means to access advanced AI tools are already developing capabilities outside formal learning environments. Others, however, may lack the financial resources, confidence, or opportunities to experiment, risking the creation of new forms of educational disadvantage. From this perspective, equitable AI adoption is not simply about purchasing licences. It is about ensuring that all students can develop AI literacy, critical judgement, and confidence regardless of their background or circumstances. Professor Thomson reinforced this argument by reflecting on Manchester's decision to provide Microsoft Copilot access to all staff and students, combining equitable access with improved security, privacy, and institutional oversight.
Human-Centred by Design Matters
Perhaps the most important message from both speakers was that building an AI-ready university starts with people, not technology. Professor Adachi argued that AI literacy is less about mastering specific platforms and more about developing the critical understanding needed to evaluate AI outputs, recognise limitations, and make informed judgements. Professor Thomson reinforced this through reflecting on this work at Cardiff University that asks a deceptively simple question: what is the most valuable human work? Rather than assuming AI should automate existing tasks, educators are encouraged to identify where human expertise, relationships, and judgement create the greatest value, and then consider how AI might support those activities. The results often reveal differing perspectives, underscoring that universities are still negotiating where human and technological contributions should intersect. This emphasis on human capability is important because it shifts the conversation away from discourses of efficiency and productivity and towards critical consideration of educational purpose.
Curriculum, Assessment and Capability Development
Curriculum and assessment emerged repeatedly throughout the discussion as critical sites of institutional transformation. Both speakers emphasised that AI capability cannot be left to chance but must be developed systematically through curriculum design, staff development, and student support. For Professor Adachi, at Queen Mary, this includes institution-wide professional learning opportunities alongside dedicated student resources focused on AI for learning and research. At Cardiff, and previously Manchester, Professor Thomson highlighted the importance of embedding AI within disciplinary contexts, reflecting how graduates will encounter AI in professional practice rather than as a standalone subject. Unsurprisingly, assessment remains one of the sector's most pressing challenges. Frameworks distinguishing between the permitted use of AI in student assessment work can help provide clarity and consistency. However, both speakers cautioned against overreliance on mechanisms for AI detection and control, arguing that academic integrity is best supported through trust, transparency, dialogue, and informed professional judgement.
The rich discussion and insight emerging from the first webinar in the “Generation AI: Empowering Creativity & Productivity Across Higher Education” series revealed that building an equitable AI-ready campus is not fundamentally about purchasing software or creating robust governance and policy. It is much more about creating the conditions and environments in which people can thrive alongside rapidly evolving technologies. Institutions have an opportunity to create more inclusive forms of digital capability, prepare graduates for AI-enabled workplaces, strengthen educational partnerships, and refocus attention on the uniquely human dimensions of learning. The message from both speakers was clear. Universities should not only be asking, "What can AI do?" More crucially, they should also be asking "What kind of learning community do we want to create?" Those institutions able to meaningfully respond this question will be best positioned to build digital ecosystems that are not only AI-ready, but genuinely equitable, human-centred, and future-focused.
These reflections will inform the ongoing “Generation AI” series as we continue exploring how institutions can build equitable, human‑centred, AI‑ready ecosystems.
