As cultural heritage institutions (CHIs) increasingly adopt digital and AI-driven tools, they encounter both new possibilities and complex challenges. Digitization and AI can enhance preservation, broaden access, and create more meaningful public engagement. Yet CHIs often struggle to evaluate and select suitable projects due to fragmented institutional priorities, limited technical capacity, and decisionmaking models that overlook cultural and social values.

This study introduces a micro-level decision-support framework tailored to help CHIs assess digitization and AI-supported projects. Developed through a three-phase mixed-method design—combining a systematic literature review, focus groups, and the Delphi technique—the framework incorporates input from professionals across Europe’s cultural and creative sectors, including representatives from ethnic minority communities. Their diverse perspectives ensured that the framework reflects not only technical and financial feasibility but also accessibility, social value, and cultural significance.

The result is a validated set of 43 evaluation criteria organized into six thematic categories: finance and investment, employment and personnel, market relevance, accessibility, social impact, and characteristics of cultural heritage objects. This framework offers a structured, context-sensitive approach for CHIs to navigate trade-offs between innovation and institutional missions. It advances theoretical understanding by integrating cultural value into project assessment and provides practical guidance for strategic decision-making. Though designed for project-level use, the framework can inform broader applications, including multi-criteria decision-making methods and institutional planning. In doing so, it supports CHIs in making inclusive, culturally grounded investments that align with both technological advances and evolving public expectations.