The advent of GenAI (Generative AI) has created a number of challenges and uncertainties for Higher Education. Much of the early discussion of these challenges has focused on what educators should do as an initial response, and on the need to maintain integrity of assessment given that GenAI can create text which is polished, and at least superficially meets the requirements of the type of essay that students are expected to produce.

This emphasis on immediate steps to adapt to availability of GenAI, and to recognise instances where approaches to assessment need to be altered, was entirely appropriate in the short term, but does not address how GenAI can fit into Higher Education in the longer term. This presentation addresses how universities can and should adapt to GenAI beyond the initial response, and how academic staff should be involved in this process. It draws on theories of change which can be applied to various innovations and on the need for multiple players within a university to accommodate the impact of this emerging technology. It is grounded in the presenters’ participation in the change process as academics, teaching in a Business School, with an interest in technology innovations and their impact on pedagogy in particular.

Among the challenges which academics and others working in higher education need to address are that it remains unclear what possibilities GenAI will offer in the longer term. It is tempting to dismiss it as a tool of limited value, for example because of its tendency to generate hallucinations, while overlooking the likelihood that these limitations will be overcome before long and indeed the experience that since their inception the current GenAI tools have already improved significantly. Similarly the level of engagement with GenAI among academics in particular varies considerably: it is likely to become increasingly difficult for anybody working in Higher Education to ignore it completely and universities’ policies on GenAI need to include some consideration of how to support staff who are reluctant to learn about it or to engage with it.

From a student’s perspective GenAI is a tool that they encounter in their everyday life and one which they can learn to use effectively. It is neither realistic nor constructive to expect students to avoid using GenAI completely and indeed to do so would lead to them developing skills which are already outdated when they graduate. Nevertheless in many disciplines students need to produce original, clear, and persuasive written work and the availability of GenAI creates new constraints around how this can be enabled and assessed. An ability to evaluate critically sources of information and to build on them is essential for university students and GenAI introduces both challenges and opportunities here, for example the need to understand prompt engineering.

University managers and those responsible for quality assurance and for determining pedagogic policies need to make decisions on how to address the use of GenAI and ensure that policies are clearly understood and agreed. Adapting to GenAI needs discussion and consensus that runs across different functions within a university and is not something which can be determined within organisational silos.

Keywords: Generative AI, higher education policy, theory of change.