by Joanna Woronkowicz
I’ve been thinking a lot about AI and its place in the cultural sector lately and what we can anticipate happening in the long-term. These are early musings—predictions rather than conclusions—based on the work I’ve been doing: running a survey of arts alumni about AI and work, collaborating on a grant project on transformative technologies, creativity, and value creation with colleagues from BI Norwegian Business School and Copenhagen Business School, leading an AI and creative industries research network through CreativePEC, and co-editing a special issue of a journal on creative work and emerging technologies. Across all of this, a few patterns keep emerging.
One thing that has struck me is that AI feels more like a fad than a long-term trend. The media hype is enormous, but when we look at how cultural organizations and artists are actually experimenting with AI, the impact seems more incremental than revolutionary. A small museum, for instance, might experiment with AI to generate multiple options for exhibit labels, or a theater company might use AI to suggest alternate seating layouts for ticketing. A visual artist might use AI to make their art more interactive. A screenwriter might use AI to come up with ideas for a story. These uses are practical and useful, but they don’t fundamentally change the creative process. My early prediction is that AI will mostly become part of the background, quietly integrated into workflows, rather than transforming the essence of creative work.
Another pattern is that AI tends to replace the less creative parts of work, not the more creative ones. Tasks like drafting, transcription, scheduling, and basic design iterations are areas where AI can provide the most value. Imagine a graphic designer using AI to generate five preliminary poster layouts, letting them focus their attention on the final composition, typography, and visual storytelling. Or consider a curator using AI to help transcribe hours of oral history interviews, freeing them to spend more time analyzing and interpreting the material. In both cases, AI supports the work, but the key artistic decisions remain human. My prediction is that this division of labor will only deepen over time, with AI increasingly handling the routine tasks while the distinctly human parts of creative practice become even more central.
Ethics and policy concerns are also top of mind. People worry about copyright, authorship, bias, and misuse. My early sense is that, as with other technological tools, these issues will be handled pragmatically and ad hoc. For example, a gallery could require that AI-generated marketing content is labeled, or a publishing house might decide that AI can assist with indexing and metadata but not with authoring final text. These solutions won’t be perfect, but they will allow creative work to continue without getting bogged down in legal or ethical paralysis. My prediction is that the sector will settle into a patchwork of workable norms rather than sweeping, definitive policies—enough structure to keep things moving, but never enough to eliminate the ambiguity entirely.
Taken together, these patterns suggest that AI will gradually embed itself into the everyday workings of the cultural sector, taking on routine tasks while leaving the core creative work to humans, and for the sector to develop practical, flexible guidelines that support its use without ever fully resolving the uncertainties it brings. In other words, AI in the cultural sector is useful and quietly transformative, but not revolutionary.
That said, I think it’s important to welcome AI as a productivity tool rather than fear it. Some disciplines or roles may see a greater effect, particularly tasks that are heavily productivity-focused, but I don’t anticipate entire disciplines or jobs being wiped out. A playwright might use AI to generate dialogue prompts for brainstorming, while still writing the final scenes themselves. A performing arts administrator might automate rehearsal schedules with AI, while the creative planning and coaching remain human-driven. AI will change how we work more than who does the work.
Finally, we are still in the early phase of adoption, which comes with instability, ambiguity, and hype. The headlines make it feel like AI is sweeping through the sector overnight, but history tells us that, like previous technological waves, this phase will pass.
Those are my predictions. Now let’s see if they’re right.