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However, existing reviews have not comprehensively addressed these recent breakthroughs and their integrated impact across the creative production pipeline. This paper addresses this gap by providing a systematic review of AI technologies that have emerged or matured since our 2022 review, examining their applications across content creation, information analysis, post-production enhancement, compression, and quality assessment. We document how transformers, LLMs, diffusion models, and implicit neural representations have established new capabilities in text-to-image\/video generation, real-time 3D reconstruction, and unified multi-task frameworks\u2013shifting AI from support tool to core creative technology. Beyond technological advances, we analyze the trend toward unified AI frameworks that integrate multiple creative tasks, replacing task-specific solutions. We critically examine the evolving role of human-AI collaboration, where human oversight remains essential for creative direction and mitigating AI hallucinations. Finally, we identify emerging challenges including copyright concerns, bias mitigation, computational demands, and the need for robust regulatory frameworks. This review provides researchers and practitioners with a comprehensive understanding of current AI capabilities, limitations, and future trajectories in creative applications.<\/jats:p>","DOI":"10.1007\/s10462-026-11494-w","type":"journal-article","created":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T07:54:24Z","timestamp":1769241264000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Advances in artificial intelligence: a review for the creative industries"],"prefix":"10.1007","volume":"59","author":[{"given":"Nantheera","family":"Anantrasirichai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Bull","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,24]]},"reference":[{"issue":"01","key":"11494_CR1","doi-asserted-by":"publisher","first-page":"485","DOI":"10.30574\/ijsra.2025.14.1.0061","volume":"14","author":"A Aggarwal","year":"2025","unstructured":"Aggarwal A (2025) Evolution of recommendation systems in the age of generative AI. 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