A Human–AI Compass for Sustainable Art Museums: Navigating Opportunities and Challenges in Operations, Collections Management, and Visitor Engagement

preprint OA: closed
View at publisher

Abstract

This paper charts AI's transformative path toward advancing sustainability within art museums, introducing a human–AI compass as a conceptual framework for navigating its integration. It advocates for human-centric AI that optimizes operations, modernizes collection management, and deepens visitor engagement—anchored in meaningful human–technology synergy and thoughtful human oversight. Drawing on extensive literature review and real-world museum case studies, the paper explores AI’s multifaceted impact across three domains. Firstly, it examines how AI improves operations, from audience forecasting and resource optimization to refining marketing, supporting conservation, and reshaping curatorial practices. Secondly, it investigates AI's influence on digital collection management, highlighting its ability to improve organization, searchability, analysis, and interpretation through automated metadata and advanced pattern recognition. Thirdly, the study analyzes how AI elevates the visitor experience via chatbots, audio guides, and interactive applications, leveraging personalization, recommendation systems, and co-creation opportunities. Crucially, this exploration acknowledges AI's complex challenges—financial, technical, environmental, ethical, societal, and practical-operational—underscoring the indispensable role of human judgment in steering its implementation. The human-AI compass offers a balanced, strategic approach for aligning innovation with cultural sensitivity, inclusivity, and sustainability. The study provides valuable insights for researchers, practitioners and policymakers, enriching the broader discourse on AI's growing role in the art and cultural sector.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00