The Evolution of Library Workplaces and Workflows via Generative AI

ChatGPT was released on November 30 th 2022, and very quickly popularized generative artificial intelligence (AI) to the extent that it is now seen as a mainstream technology and used by many. However, this mainstreaming and popularity has also resulted in a hype, thereby overwhelming us by a wide range of opinions and news related to its current and future applications. While we can test generative AI applications and read news about their added value, it might be hard to envision the short-, medium- and long-term impact of these tools on library operations, resources, and services. Reflecting on how libraries and their existing workflows are evolving alongside the rise of generative AI is intriguing, yet extremely challenging due to the rapid development of the technology. This is further complicated by the variation across each library’s organization, management, and use. Indeed, even two libraries in the same institution might have a different approach regarding collection management, curation, user engagement, and technology integration. These differences can be further amplified by library size, disciplinary focus (e.g., university library, medical library, law library), services offered (e.g., education and training, evaluation), communities served (e.g., students, medical trainees, researchers, faculty, public), overall approach to technology, as well as their budget. Each library is made up of several units with specific goals and responsibilities. The same technology may have a different impact on each department of a library, as well as each employee, depending on their role and background. As a result, despite various opportunities and challenges presented by generative AI, librarians should consider charting their own personal roadmap to learn about and familiarize themselves with this technology based on their unique circumstances, interests, and needs.