Generative artificial intelligence (AI) is transforming the production, evaluation, and economic valuation of creative work. However, existing research presents mixed findings on whether AI enhances or constrains human creativity, raising important questions about its implications for sustainable development. This narrative thematic review synthesises 44 scholarly works published between 2022 and 2026, supplemented by foundational literature and relevant institutional reports and policy documents. The evidence is examined across four dimensions of sustainability: social, cultural, economic-institutional and environmental. The reviewed evidence suggests that generative AI can enhance creative performance in certain tasks, with particularly notable benefits for users exhibiting lower baseline creative performance. However, findings from open-ended and multimodal tasks indicate that human creativity retains important strengths, particularly in originality and contextual interpretation. Individual performance gains may coexist with reduced collective diversity, perceived losses of authenticity, over-reliance on AI-generated outputs, and emerging economic pressures on creative workers. These outcomes appear to depend on task characteristics, user expertise and AI literacy, levels of automation, and organisational governance. Environmental sustainability remains the least investigated dimension, as the reviewed creativity-focused studies do not directly measure the energy consumption or carbon footprint of AI-assisted creative activities. Drawing on this synthesis, the review proposes a four-dimensional conceptual framework for human-centred sustainable creativity and identifies five conditions influencing whether generative AI functions as an advantage or a barrier. The findings suggest that AI's contribution to sustainable development is conditional rather than inherently beneficial or harmful, highlighting the importance of human agency, responsible governance, cultural diversity, and environmental awareness.
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Vüsal Hüseynov (2026) studied this question.
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