Advances in Artificial Intelligence: A Review for the Creative Industries

TL;DR

This review comprehensively discusses recent AI breakthroughs like generative models and LLMs, highlighting their transformative impact on creative industries and the shift towards integrated, multi-task AI frameworks.

Contribution

It provides a systematic overview of recent AI advancements since 2022, emphasizing their applications, integration, and implications in creative industries.

Findings

Transformers and LLMs enable advanced content generation.

Unified AI frameworks are replacing task-specific solutions.

Human oversight remains crucial for creative AI applications.

Abstract

Artificial intelligence (AI) has undergone transformative advances since 2022, particularly through generative AI, large language models (LLMs), and diffusion models, fundamentally reshaping the creative industries. 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-shifting 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.