Morning, Friday, 11th December 2026
Online
This conference will examine next steps for artificial intelligence in higher education in the UK.
It will be a timely opportunity to consider key developments and emerging issues as AI adoption progresses from individual use by staff and students, alongside experimentation across teaching, assessment and institutional practice, towards more established approaches at institution level. We expect discussion to bring out latest thinking on responsible adoption and oversight, implications for academic standards and the student experience, priorities for developing institutional and staff capability, and the changing role of AI in higher education research and innovation.
Overall, it will bring stakeholders and policymakers together to consider implications of emerging sector evidence, including the forthcoming Office for Students and Advance HE’s joint research into the use of AI across HE, alongside concerns identified in the Quality Assurance Agency’s The Perfect Storm: AI, Assessment and a Sector Under Pressure. Discussion will consider what findings mean for institutional approaches as AI use becomes more widespread, including consistency of policy and practice, assessment and academic integrity, student expectations and outcomes, and the capability and support needed by staff and students.
The agenda will examine practical priorities for moving from isolated pilots and variable practice towards sustainable institution-wide adoption. Areas for discussion include governance and accountability, procurement and assurance, appropriate human oversight, and approaches to managing risk while enabling effective use of AI. Further discussion will look at implications of financial and organisational pressures, access to expertise and infrastructure, and questions of equality, accessibility and differing levels of access to AI tools and support.
The conference will also consider how these developments sit within the wider direction of policy for AI, skills and research, including implementation of the Post-16 Education and Skills White Paper in England, the AI Opportunities Action Plan: One Year On, and priorities set out in UKRI’s AI Research and Innovation Strategic Framework and AI for Science Strategy. We also expect discussion on differing approaches across the four nations, and the role of HE in developing AI skills and talent, supporting AI-enabled R&I, and contributing to long-term national capability.
Policy, regulation, institutional governance & assurance
Sessions will assess practical approaches to accountability and oversight as AI moves from individual use into institutional systems, including the respective roles of government, regulators, sector bodies and institutional leaders in shaping approaches to AI adoption across HE.
Overall, areas for discussion include:
- regulatory approach: the OfS principles-based model - scope for innovation and experimentation - what guidance is needed to provide sufficient clarity for providers
- institutional strategies: moving beyond isolated pilots - accountability at board and executive level - meaningful human oversight of AI-supported processes
- sector consistency: common principles alongside institutional autonomy - what a shared baseline might cover - variation in published policies
- procurement & assurance: contractual safeguards and auditability - supplier oversight - implications of dependency on a small number of suppliers
- data protection & security: safeguarding student and research data - cyber resilience - transparency around how systems are trained and monitored
- challenge & redress: correcting AI-supported decisions - routes for students and staff to contest outcomes - evidence and record-keeping
Teaching, assessment & the student experience
Discussion will assess approaches to academic integrity that are proportionate, fair and evidence-based, as well as addressing variation between institutional policies, practice and student understanding.
Overall, areas for discussion include:
- assessment redesign: how existing approaches may need to change - practical considerations for workloads and budgets - approaches to evidencing independent work and legitimate assistance
- clarity & consistency: acceptable use and disclosure - variation between departments and modules - qualification credibility and confidence in awards
- oversight & scrutiny: limitations of detection software - proportionate, evidence-based integrity processes - student anxiety about false accusation
- use in pedagogy: feedback, tutoring and personalised learning - AI in student support services - evaluating effects on learning, attainment and retention
- accessibility & inclusion: assistive use within academic conduct rules - disabled and neurodivergent students - student involvement in development of institutional approaches
- access & bias: paid tools, devices and connectivity - addressing inequalities, including differential performance for particular groups and international students
AI literacy, staff capability & graduate outcomes
The agenda will look at how capability can be embedded across disciplines - for students, and for the staff expected to teach, assess and support them - and how to meet changing employer needs.
Overall, areas for discussion include:
- AI literacy: preparing students for an AI-enabled labour market - technical, critical and ethical capability across subjects and levels - foundational knowledge - independent judgement
- staff development: confidence, training and workload - professional autonomy and changing roles - institutional support for professional services staff alongside academic colleagues
- graduate outcomes: changes in entry-level recruitment - skills sought by employers in early-career hires - opportunities for applied learning and industry engagement
- employer engagement: placements, traineeships and applied learning - TechFirst, TechLocal and related programmes - collaboration on curriculum content
Research, innovation & AI capability
Sessions will assess implications of AI for research, knowledge exchange and innovation in the context of priorities set out in UKRI’s AI Research and Innovation Strategic Framework, including implications for funding and the productivity potential of AI-enabled research, as well as what access to compute, data and expertise looks like for institutions of different sizes and missions.
Overall, areas for discussion include:
- research practice: AI-enabled discovery and interdisciplinary collaboration - evidence for productivity claims - training and support for researchers
- research integrity: authorship and disclosure - reproducibility and peer review - transparency
- data, compute & expertise: access to national facilities and the AI Research Resource - research data security - intellectual property in industry partnerships
- funding priorities: delivery of the UKRI framework - AI for Science missions - responsible AI-enabled research - aligning institutional strategy with funder expectations
- commercialisation & place: knowledge exchange and spinouts - links with emerging AI Growth Zones and regional development - developing AI skills and talent pipelines
- cost & sustainability: energy, licensing and infrastructure costs - what smaller and specialist providers can realistically access
All delegates will be able to contribute to the output of the conference, which will be shared with parliamentary, ministerial, departmental and regulatory offices, and more widely. This includes the full proceedings and additional articles submitted by delegates. As well as key stakeholders, those already due to attend include a parliamentary pass-holder from the House of Commons and officials from the Department for Work and Pensions; Information Commissioner's Office; and Intellectual Property Office.
