How GenAI can amplify co-creation in higher education

GenAI tools are engineered to eliminate uncertainty. In training, they are penalised just as harshly for admitting they don’t know the answer as for providing incorrect information. And their tendency to people please (sycophancy) often means they mirror our thinking rather than stretch it, unless we deliberately invite dissent and uncertainty into the exchange. Part of the challenge is structural: GenAI tools sound certain when they should not. Asking for confidence, caveats and limits helps us read outputs with a grain of salt. 

Co-creation forces staff and students to ask difficult questions and hold each other accountable as equals. Interactions that happen during the process are the opposite of falsely reassuring conversations with GenAI. Genuine co-creation can be messy, but it is this messiness that makes it special and generative. Insights and clarity emerge through challenging each other and iteration, not quick answers. 

But we can use GenAI to support co-creation. It can help us quickly interpret insights, brainstorm ideas, prototype initiatives, run scenarios and visualise personas. We firmly believe that these tools can help us reallocate our time and resources, but more importantly, reaffirm the centrality of human relationships in higher education. Maintaining a human-centred mindset is essential: designing with, not just for. But this is not easy, and we need tools such as the Designing Together card deck, an intentionally low-tech resource to support co-creation, to help us hone this mindset. 

• Spotlight guide: The practicalities of co-creation with students
• Co-creation of curricula with students – a case study
• Embracing co-creation through experiential learning

The three tensions of using AI in co-creation

Since launching the cards, we have had countless conversations with students and colleagues about AI’s growing role in co-creation. We distilled these into three tensions. 

• Dialogue v debate. Dialogue is more productive than debate when engaging in collective sense-making amid uncertainty. We recommend adopting the “building to think, not thinking to build” mindset, as explained in Tim Brown’s TED Talk on design. It challenges us to not be paralysed by uncertainty or endless debates but to just get going. This approach helps us think about both the problems and possible solutions that emerge in the collaborative process, rather than hiding away to focus on one grand solution that may or may not work. 
• Patience v urgency. In pressurised environments, treating everything with urgency becomes the norm. But patience is one of the most underrated innovation ingredients. AI can speed things up, but for learning and co-creation to happen, we need to slow down. Time saved is best reinvested in listening and framing challenges together, exchanging and discussing feedback and having more conversations that build belonging. These increase productivity and quality of outputs, which is precisely why we should create scaffolds rather than shortcuts. Moving with patience allows for serendipity, joyful collaboration and care.
• Trust v distrust. Many conversations about how AI is being used in higher education are about distrust, especially towards students. But distrust doesn’t always make us critical thinkers; sometimes, whether intentionally or not, it can become a tool of oppression. Trusting someone’s experience is genuine, honouring it and taking it into account when creating solutions – this is inclusive.

To use AI successfully in co-creation processes, we need to build up not just AI literacy, but AI fluency, that is interacting with AI in ways that are effective, efficient, ethical and safe, and use it to build trust, not control, according to AI company Anthropic. Intentional use of AI can help us exchange and develop good practice faster and build trust and empathy. 

Designing together

We don’t know how AI will affect higher education over the coming years. We do not wish to be stuck in endless debates that stop us from experimenting and learning. Neither do we wish to be swept up by the temptation to prioritise efficiency, a path that risks homogenising data, stifling innovation and deskilling in critical thinking, observation, networking and experimentation.

When it comes to thinking about AI and co-creation in higher education, the question isn’t, “Should AI support our work?” but “How might we co-create its contributions?” Nor is it, “What can AI do for us?” but “How might we co-create our work, questions and solutions with AI?” We must act strategically. Here’s how:

• Prioritise dialogue by examining how co-creation currently happens. Think about where students and staff can explore ideas together, rather than simply defend positions or respond to predetermined questions or agendas. Do this with tools such as the Designing Together cards, “Listening Rooms” and “friendship as method”. AI can help teams work with what emerges by organising contributions, connecting themes and introducing alternative perspectives, but participants should remain involved in interpreting the findings. You can also turn AI-generated themes into prompts for further conversation. 
• Practise patience by mapping where insights get delayed, fragmented or overlooked, and identify where AI could add value. For example, when you need to process student feedback quickly, AI can help. But faster analysis does not necessarily produce better understanding. Platforms such as Explorance and Unitu work well, but centre the staff needs and voices, too. 
• Build trust by involving students as partners in deciding how to use AI to frame the problem, selecting tools, testing prompts, reviewing AI-generated themes and establishing how findings should inform action. Start with a small-scale pilot experiment or extend an existing partnership. Pay attention to how you close the feedback loop and update students on what was heard, what changed, what could not change and why.

Co-creation is a key ingredient for innovation in teaching and learning. For it to work, we need to create space for dialogue that cultivates patience and trust. AI can amplify the impact, but empathy must be our anchor. The future of co-creation relies on it.

Bo Kelestyn and Jess Humphreys are associate professors at the University of Warwick. Dmytro Chumachenko is associate professor at the Kharkiv Aviation Institute in Ukraine. 

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