Beyond Technical Implementation: A Systematic Review of Artificial Intelligence Applications in Museum Learning

This preprint of a systematic review examines the intersection of generative artificial intelligence and museum learning by analysing 27 texts published between 2022 and 2025. The study addresses three research questions: which AI-driven technologies are being applied in museum learning contexts, which educational use-cases they address, and how these dimensions interrelate. Using a mixed-methods approach combining quantitative content analysis with qualitative synthesis, the review identifies four dominant use-cases for AI in museum learning - increasing the effectiveness of learning (1), personalisation of visitor experience (2), social inclusion and community building (3) and developing digital literacy (4). A scoring analysis evaluating technological robustness relative to educational quality shows that most implementations (n=18) feature basic technology and learning experiences with limited sophistication. The study reveals opportunities for museums to be more active in developing applications and that future research should prioritise genuine interdisciplinary collaboration alongside rigorous operationalisation of learning outcomes.