A review of Generative AI in Creative Industries and Cultural Professions

How is Generative AI transforming creative industries and cultural professions? What are the attitudes of visual artists, writers, performers, designers, and architects around GenAI? How are they using large language models and other discipline-specific tools their professional work? A review of 57 studies shows how creative professionals aren’t simply embracing or rejecting AI—they’re developing sophisticated strategies to maintain control while leveraging new capabilities. Younger professionals see AI as just another digital tool, while senior practitioners worry about their hard-won expertise becoming obsolete.

The more a creative field values embodied practice and “pure” creativity (like fine arts, literary fiction, or classical music), the more it resists AI. Meanwhile, commercially-driven fields embrace it for efficiency. Visual artists fear being drowned out by the sheer volume of AI art; writers struggle with AI’s tendency toward cliché; performers uniquely embrace AI’s unpredictability as creative fuel; architects worry about cultural homogenization.

While universities emphasize critique and traditional craft, industry increasingly demands AI fluency. However, rather than simply following industry trends, educational institutions can shape the future of creative practice by teaching students traditional skills and AI literacy as complementary tools; developing critical and “adversarial creativity”—how to subvert, resist, or creatively appropriate AI systems to maintain human agency and cultural diversity; creating protected spaces for traditional crafts and embodied practices that risk being lost, ensuring creative divergence counters digital homogenisation. Rather than just preparing students for current industry practices, creative education can actively shape what creative professions become. By teaching both collaboration with and resistance to AI, we can ensure the next generation of creatives maintains human agency, cultural diversity, and meaningful practice in an AI-saturated world.

Read more here.

Tsao, J., Liang, C., Nogues, C. Wong, A. (2025) Perceptions and integration of generative artificial intelligence in creative practices and industries: a scoping review and conceptual model. AI & Society. https://doi.org/10.1007/s00146-025-02667-2

Keywords: Generative artificial intelligence, creative industries, creativity, Human-AI collaboration, creative practice