Embracing GenAI in art and design teaching
The rise of GenAI has significantly disrupted the creative industry and art and design higher education. As a dual professional, I have observed and experienced the implications of GenAI both in the industry and within the course where I teach. The panic is palpable in academia and has plunged educators into a period of uncertainty and rapid pedagogical change, where responses often oscillate between optimism and concern. There is also broader discourse in the creative sector about whether AI might turn aspects of creativity into a luxury good, privileging those with access and understanding of these tools whilst marginalising others (Alagiah, 2024). Ultimately, we cannot stop GenAI and automation in the creative fields, but we can reframe how we think, create, and operate in collaboration with AI.
Watching the recorded guest lecture and workshop with Chris Rowell (2026) has prompted me to critically reflect on my own position regarding the use of GenAI, more specifically in the studio-based practice where I teach. At the BA of Graphic Branding and Identity, we teach students to develop verbal and visual identities for organisations that are meaningful and unexpected, based on societal and audience-led contexts. GenAI can, and has been used to develop such brand identities by students, albeit with varying degrees of criticality and success.
As technology evolves, taste and discernment become increasingly central to creative value, as these are human capacities that cannot be fully delegated to machines (Goodspeed, 2024). Furthermore, recent studies suggest that GenAI can enhance creative processes by supporting ideation, iteration, and experimentation, particularly when students actively engage with prompt development and critical evaluation of outputs (Lee, 2025), yet this critical engagement is not currently embedded within the curriculum, which could contribute to the widening of the gap in terms of industry readiness.
In my view, it is our role as educators to guide students on where their input starts and stops and when to allow GenAI in. This shifts the focus from restricting AI use to developing “AI literacy,” where students critically assess outputs, understand limitations, and maintain authorship over their work, positioning them as active agents rather than passive users of technology.
I will most certainly use the Value Spark Cards (Rowell, 2026) to structure and inform our teaching in relation to GenAI, and to help navigate both staff and students through the perils and opportunities of using GenAI in their practice. Like the inevitability of self-driving cars, the use of GenAI is looming, and we must face its reckoning head-on to best support students on how to embrace AI in their practices, creatively, ethically and sustainably. In this sense, GenAI should be approached not simply as a tool, but as a potential creative collaborator that requires critical oversight.
In the words of David Lee, CCO of Squarespace, “Creativity might be the only job left in the future, full stop”. This aligns with industry forecasts, such as the World Economic Forum’s Future of Jobs Report (2020), which emphasises that creativity, critical thinking, and problem-solving are projected to become the most in-demand human skills as automation and AI take over routine tasks (World Economic Forum, 2020).
AI is reshaping the role of design and creative practitioners to become more ideas-led and craft focused, taking away menial and repetitive tasks. Some might see this as a risk, however, I increasingly believe that GenAI can accelerate workflows and support rapid prototyping, allowing designers to focus more on higher-level creative decision-making and conceptual thinking.
Although my knowledge is still limited, I am beginning to actively experiment with and integrate GenAI within my teaching practice. For example, I have challenged students to design automated brand identities using AI tools, as well as introducing rapid prototyping through prompt writing, which has opened up new discussions around authorship, originality, and creative control. I believe the role of the designer is not in danger, but rather it has been reconfigured and, in some cases, “moved upstream” (Alagiah, 2024) – from maker to critical orchestrator of tools, processes, and meaning.
References
Alagiah, M. (2024) ‘Will AI turn human creativity into a luxury good?’, It’s Nice That, 31 July. Available at: https://www.itsnicethat.com/articles/pov-will-ai-turn-human-creativity-into-a-luxury-good-creative‑industry‑310724 [Accessed: 18 March 2026].
Art, Design & Artificial Intelligence: An educator’s toolkit (2024). Available at: https://figshare.com/articles/online_resource/Art_Design_Artificial_Intelligence_An_Educator_s_Toolkit/30374065 [Accessed: 18 March 2026].
Goodspeed, E. (2024) ‘Taste, technology and the future of art’, It’s Nice That, 28 February. Available at: https://www.itsnicethat.com/articles/elizabeth-goodspeed-column-taste-technology-art‑280224 [Accessed: 18 March 2026].
Lee, C.-W. (2025) ‘Application of generative artificial intelligence in design education’, Engineering Proceedings, 98(1), p. 29. Available at: https://www.mdpi.com/2673-4591/98/1/29 [Accessed: 18 March 2026].
Rowell, C. (2026) Introduction to Art, Design & Artificial Intelligence. Guest lecture delivered at University of the Arts London, 11 March.
World Economic Forum (2020) The Future of Jobs Report 2020. Geneva: World Economic Forum. Available at: https://www.weforum.org/reports/the-future-of-jobs-report-2020 [Accessed: 18 March 2026].
