Noëlle Quénivet and Neeti Shikha
On 3 September 2026, colleagues from across UWE Bristol gathered for the AI in Education conference, a day dedicated to exploring how artificial intelligence is reshaping teaching, learning, assessment and academic practice. The event brought together academic and professional services colleagues from different Schools such as engineering, social sciences, business and law to share experiences, discuss challenges and consider how higher education can respond constructively to a rapidly evolving technological landscape.
From experimentation to integration
From the outset, the conference emphasised that AI is no longer a future possibility but a present reality. In his opening remarks, Dr James Lee, Pro-Vice Chancellor and Head of the College Health, Science and Society, reflected on UWE Bristol’s AI journey, noting that the institution has moved beyond experimentation towards embedding AI within curricula and supporting staff in developing their capabilities. James Lee made a particularly striking observation that AI should not be regarded as a passing trend, but as the next stage in the evolution of teaching and learning. The point invites an almost Darwinian reflection on adaptation; those institutions, educators and students best able to adapt to this changing environment may be the ones most likely to survive and thrive within it.
The conference itself was framed around key themes including equitable access to AI, curriculum development and staff support. These themes were identified by conference participants before the event provided a useful backdrop to the day’s discussions. Mark Shand, Senior Learning Technologist, explained that colleagues expressed interest in using AI to work more efficiently, improve teaching and learning, and rethink assessment in ways that maintain academic integrity while acknowledging the realities of an AI-enabled world. At the same time, concerns around ethics, risk, changing professional roles and the need for practical skills training featured prominently throughout the programme. Colleagues were then invited to attend a variety of panels run concurrently. In this blog post, we are sharing our thoughts on panels we attended though this might not truly capture the wide range of themes addressed at the conference.
AI writing feedback: research findings and opportunities for practice
This session, held by Dr Sarah Gillie and Jackie Chelin, discussed research findings on the integration of AI-supported writing feedback tools such as Studiosity and ways in which students engage with automated feedback. They noted that these tools are most effective when positioned not as substitutes for human support, but as part of a wider academic support ecosystem, complementing institutional resources and opportunities for in-person guidance. In contrast, students who did not make use of Studiosity relied more on AI and other digital tools. Discussions underscored the importance of helping students understand and interpret feedback, recognising that comments can sometimes seem mysterious or overly summative without opportunities for dialogue and reflection.
Assessment and academic integrity
This session, led by Dr Antony Hill, Dean of Learning and Teaching at the College of Health, Science and Society, addressed what we would consider the most pressing concerns facing higher education. Colleagues considered how generative AI challenges traditional assumptions about authorship, originality, expertise and assessment validity. The discussion gradually moved beyond concerns about cheating to question a more fundamental premise regarding the purpose of assessment itself. As several participants noted, if assessment remains focused solely on outputs, institutions may struggle to distinguish between genuine learning and AI-generated work. Colleagues agreed that there is need for deeper conversation around assessment design, transparency and judgement, with a strong emphasis on evaluating students’ learning processes rather than merely the final product.
AI, employability and the future of work
This session, chaired by Dr Frano Barbic, extended these discussions beyond the classroom. Panellists (Dr Kamran Soomro, Dr Christopher Lipp, Michal Bobula, Nhi Ho and a PGR student from the College of Arts, Technology and Environment) stressed that while AI will undoubtedly transform workplaces, human capabilities remain central. Critical thinking, deep understanding, sound judgement and interpersonal skills were repeatedly identified as qualities that cannot be outsourced to technology. Indeed, participants suggested that competitive advantage increasingly lies in human relationships, creativity and the ability to make informed decisions in complex situations.
Universities therefore now face a dual responsibility: preparing students to use AI effectively while simultaneously ensuring they retain the intellectual foundations necessary to evaluate and challenge AI-generated outputs.
AI, equity and the student experience: Understanding EDI opportunities and challenges and supporting diverse learners
The roundtable led by Steffie Denton explored the opportunities and challenges that AI presents for equity, diversity and inclusion in the student experience. Discussion considered inequalities in access to AI, differences in students’ experiences of using these tools, and how disclosure of AI use may sometimes introduce bias into assessment and evaluation. Audience questions prompted reflection on how institutions might make AI use more inclusive and support diverse learners more effectively.
The discussion also recognised that AI systems themselves may reproduce or amplify biases embedded in their training data. Together, these issues highlighted the layered relationship between student experience, institutional practices and technological bias. While the roundtable generated valuable discussion, several questions remained open, particularly around how institutions can translate principles of equity into practical approaches to AI use and assessment.
Reflections
A recurring theme throughout the day was the increasing importance of AI literacy. The challenge is not only to determine whether students are using AI, but also to help them (as well as colleagues!) understand when, why and how these tools should be used.
The conference made us rethink about our response to AI in education which should not be framed only around risk, detection or efficiency. Instead, it requires us to think carefully about what kinds of learning experiences we want students to have, and which intellectual skills we want them to retain and strengthen in an AI-enabled environment.
Participants observed a tendency to treat AI as synonymous with ChatGPT, when in reality the landscape includes a wide range of tools designed for different purposes.
Developing the capacity to select appropriate tools, verify outputs and critically evaluate information emerged as a crucial graduate attribute for the future.
For legal educators, these discussions are particularly relevant. The legal profession is already integrating AI into research, drafting and administrative processes. Yet legal reasoning, ethical judgement and critical analysis remain indispensable (read the blog post by Dr Neeti Shikha). The conference served as a timely reminder that our task is not to resist technological change but to ensure that students learn to engage with it thoughtfully, responsibly and critically.
The AI in Education conference demonstrated that institutions are moving beyond questions of whether AI should be used and towards more constructive discussions about how it can be used well. The most valuable takeaway was perhaps the simplest: technology may change rapidly, but the core purposes of higher education, developing understanding, cultivating critical thinking and preparing students for meaningful professional lives, remain remarkably constant. AI changes the context, but not the underlying mission.
PS: Copilot was used to structure handwritten notes taken during this event and the final version was edited using Grammarly