This paper provides a comprehensive systematic review of the current state of artificial intelligence (AI) applications in museums, the challenges encountered, and potential future directions. The review synthesizes literature demonstrating how AI technologies—encompassing machine learning, natural language processing, computer vision, and generative models—are transforming key museum functions. These include conservation and restoration, exhibition and narrative design, education and accessibility, and the development of smart museum infrastructures for enhanced visitor experiences. Findings indicate that AI offers significant potential to improve operational efficiency, democratize access to cultural heritage, and foster participatory, co-creative engagement between institutions and audiences. However, the integration of AI also raises critical ethical and practical concerns regarding authenticity, curatorial authority, data bias, intellectual property, privacy, and equitable access. The paper concludes that the future trajectory of AI in museums will depend less on technological sophistication and more on the development of robust ethical frameworks, interdisciplinary collaboration, and thoughtful institutional choices that align with the core mission of museums as custodians of culture and public educators.
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