AI implementation is part of the digital transformation efforts of National Libraries. To understand what the challenges are and derive recommendations for other libraries, we researched the AI implementation. Based on 90 interviews with library and AI experts, we identified ten European National Libraries and included the Library of Congress and the British National Library in our case analysis. Here, we derive the challenges that National Libraries face when implementing AI technologies. Based on these insights, we provide recommendations for libraries that plan to also implement AI solutions in their organisations. This chapter focuses on sustainable governance structures that ensure long-term strategic alignment of funding and implementation goals, the promotion of technical independence of international providers through internal competence and upskilling efforts, and the involvement of information specialists and users to ensure adoption and acceptance of AI tools. Furthermore, we highlight the importance of collaborative and interdisciplinary approaches as well as transparency, responsible data management, and ethical AI.

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Recommendations for the AI Implementation in Libraries

  • Ines Mergel,
  • Justus Kühler,
  • Anna-Lea Schumann,
  • Carsten Schmidt

摘要

AI implementation is part of the digital transformation efforts of National Libraries. To understand what the challenges are and derive recommendations for other libraries, we researched the AI implementation. Based on 90 interviews with library and AI experts, we identified ten European National Libraries and included the Library of Congress and the British National Library in our case analysis. Here, we derive the challenges that National Libraries face when implementing AI technologies. Based on these insights, we provide recommendations for libraries that plan to also implement AI solutions in their organisations. This chapter focuses on sustainable governance structures that ensure long-term strategic alignment of funding and implementation goals, the promotion of technical independence of international providers through internal competence and upskilling efforts, and the involvement of information specialists and users to ensure adoption and acceptance of AI tools. Furthermore, we highlight the importance of collaborative and interdisciplinary approaches as well as transparency, responsible data management, and ethical AI.