The next chapter of libraries is likely to be defined by how well human expertise and AI are blended. By balancing automation and human skills, promoting digital literacy, and collaborating with the wider academic community, librarians can ensure that AI enhances their mission, not replaces it.
The rapid rise of artificial intelligence (AI) triggered a spectrum of perspectives about the future of work, particularly in knowledge-intensive fields. At one extreme, doomsday predictions suggest that AI will impact every facet of knowledge work and massively displace jobs. On the other end are dismissive voices, downplaying AI as another technology hype that will wear off. In between, many—including librarians—see AI as an exciting opportunity that opens up new possibilities.
A balanced view comes from Professor Karim Lakhani of Harvard Business School, who offers a middle ground. According to Lakhani, AI isn’t going to replace humans outright. Instead, those who skillfully integrate AI into their work will outpace those who don’t.
This line of thinking can be particularly relevant in the context of academic libraries, suggesting that librarians who use AI capabilities effectively will gain an edge in nearly every aspect of their work. Libraries and librarians who will master AI tools might find valuable support in areas ranging from labor-intensive work to strategic data-driven decision-making. Various AI tools in the market already offer support in areas such as cataloging, research discovery and analytics, learning assistants, and more. As these tools evolve, libraries might discover new ways to increase their productivity and reinforce their value to research and learning.
Technological revolutions have prompted fear, excitement, and, at times, disillusionment. Libraries have lived through this cycle before—most notably during the rise of search engines and the changes they brought to content discovery and access. Early fears that libraries would become obsolete gave way to the realization that they have a critical role in the digital age. Google (and others) didn’t replace libraries. Arguably, by embracing change, libraries sustained and evolved. The key to their ongoing relevance was their ability to adapt while remaining rooted in their core mission of providing access to trustworthy information.
As we face the AI revolution, the responsible application of AI in academic settings will be central to libraries’ success. Identifying the right balance between automation and human oversight, designing AI solutions that genuinely meet the needs of scholarly communities, and maintaining the ethical and intellectual rigor libraries are known for will determine their continued role as stewards of knowledge in an AI-driven future.
This article examines the key areas where librarians’ expertise is essential for driving meaningful impact.
The first step in implementing AI is identifying where it makes a difference in relation to libraries’ core mission, such as research discovery, student outcomes, and libraries’ own productivity. Librarians’ experience is key to ensuring that AI enhances—rather than disrupts—core functions. This process begins by mapping and prioritizing AI use cases according to their potential value, both in terms of strategic contributions and operational efficiencies.
For instance, AI can help with core librarianship tasks. It allows librarians to devote more time to advancing students’ literacy skills, supporting early-career researchers in choosing a research topic, or assisting them in complex literature reviews. On the strategic end, AI-driven analytics can help librarians understand usage patterns and tailor collections to better meet user needs.
The Pulse of the Library survey from Clarivate sheds light on the areas where AI applications are currently deemed most valuable:
Implementing AI in academic libraries requires a balance of practical improvements and strategic innovation. Through discussions with library professionals, we’ve identified several common themes: advancing existing practices, introducing transformative new services, accelerating productivity, and advancing DEI goals. The focus on each will vary depending on each library’s specific goals and context. Throughout, human expertise remains central, with AI as a supportive tool.
Advancing with AI
AI can be a powerful enhancer for existing library services. For example, integrating natural language search capabilities helps simplify Boolean queries for students; compiling data from various sources into a single, user-friendly format makes information more accessible for researchers; similarly, AI can streamline literature review processes, enabling quicker, more comprehensive searches across vast data sets. These enhancements focus on making library tools more intuitive and practical, ultimately making library services more compelling vis-à-vis non-academic AI tools.
Transforming with AI
AI has the potential to create entirely new ways of conducting research and enhancing learning. Systems that allow users to “converse” with data can uncover trends and narratives in ways once unimaginable. AI can also guide researchers through complex tasks, ensuring the integrity of their work and countering misinformation. AI can transform student literacy by proactively guiding them through assignments and readings, turning potential misuse into a powerful educational tool. By harnessing this transformative power, libraries can boost their institutional impact.
Accelerating productivity with AI
On the practical side, AI excels at automating essential but time-consuming tasks like metadata management, often a bottleneck in library operations. It can also improve patron support by swiftly finding information or integrating data from multiple systems. Additionally, AI can optimize acquisition processes, helping libraries better allocate resources and tailor collections to the evolving needs of faculty, researchers, and students. This frees librarians to focus on strategic work, with AI working in the loop to handle routine tasks.
Advancing DEI
AI presents a unique opportunity to enhance Diversity, Equity, and Inclusion (DEI) efforts. By automating processes at scale, libraries can deliver a consistently high level of service to all users, regardless of background or access to resources. When properly applied, AI can help create more equitable access to knowledge, improving accessibility and ensuring that underrepresented groups receive the same high-quality support as others.
As AI becomes more integrated into library services, it’s essential to strike the right balance between machine autonomy and human judgment. While AI can handle many processes efficiently, human oversight is crucial to upholding academic integrity in every aspect of library services. Establishing clear guidelines is vital to achieving this balance and safeguarding the core values.
Defining AI principles is essential in aligning with the library’s mission of upholding academic integrity and equitable access to information. These principles generally fall into three key areas:
Transparency
Libraries should ensure that AI tools are transparent about the content they use. This means guaranteeing that the sources used to generate information are academically sound and providing users with easy access to cited works. This transparency helps maintain trust in the information supplied by AI-driven systems.
Ethics
AI tools must be designed with ethical considerations, including measures to minimize misinformation and mitigate issues like hallucinations and bias. Ensuring the ethical application of AI safeguards the quality and reliability of the information users receive.
Security
Libraries need to ensure that AI tools uphold strict data privacy standards. This means protecting user data while adhering to the evolving global regulations around AI and privacy. Maintaining security ensures that users feel safe engaging with AI-powered library services.
One of the main challenges in implementing AI tools in any domain is ensuring the quality and reliability of their outputs. Traditional quality assurance techniques don’t apply to large language models (LLMs), as their responses can be inconsistent and context-dependent. Human testing, while effective, is time-consuming and impractical for ongoing assessment. This means new methods and metrics are needed to evaluate AI’s performance.
Partnering with vendors
While vendors have the primary responsibility for testing AI tools, libraries play a crucial role in advising and collaborating on evaluating AI outputs. Libraries often have the opportunity to guide product development by participating in beta programs, gaining early access to AI tools and helping to establish frameworks for assessing them, with a focus on accuracy, relevance, and ethical implications. By providing insights from real-world use, libraries can help vendors refine these tools to better align with academic standards.
User feedback
Libraries can also facilitate user feedback, gathering input from students, faculty, and researchers to inform AI vendors about their tools' use. This feedback loop can help continuously improve and adapt AI solutions to meet the specific needs of library users.
AI performance metrics
Technology vendors and user communities are still in the early stages of defining clear metrics to measure AI’s effectiveness. While key factors such as accuracy, relevance of results, and ethical compliance are critical, these benchmarks will naturally evolve. Ongoing collaboration between libraries and vendors will be essential in developing these metrics.
As AI becomes more integrated into academic life, upholding integrity in research and learning is critical. Libraries are essential in helping students and faculty use AI tools effectively and understand their limitations and ethical implications.
Promoting AI literacy
AI-generated information can be both a valuable resource and a potential pitfall. Libraries, with their deep understanding of academic rigor, are uniquely positioned to help users develop the skills to assess AI content critically. This includes teaching users to differentiate between reliable outputs and those that may be flawed or biased. It may also include prompt design, where librarians can guide users in crafting effective prompts to improve the relevance and accuracy of the results they receive.
Educating users
Similarly, libraries can offer guidance for students and faculty about trusted AI tools. This includes training on how to use these tools effectively and understanding their limitations. By providing this education, libraries can empower users to be more effective and make informed decisions when using AI.
Collaboration has always been at the heart of libraries’ work, making the development of AI best practices a natural extension of their mission. Libraries are already deeply connected with peer institutions, academic organizations, and vendors, and this collaborative spirit is key to ensuring AI is used responsibly.
As AI becomes more deeply integrated into academic environments, librarians’ role is essential. By embracing AI, librarians can enhance their roles as critical facilitators of knowledge, leveraging technology to improve the user experience while ensuring that human judgment remains at the core of research and education.
The next chapter of libraries is likely to be defined by how well human expertise and AI are blended. By balancing automation and human skills, promoting digital literacy, and collaborating with the wider academic community, librarians can ensure that AI enhances their mission, not replaces it. This thoughtful integration of AI will shape the future of academic libraries, keeping them at the heart of the institutions they serve.
This article draws on the Clarivate webinar session Demystifying AI and what it means for libraries.
To learn more about Clarivate Academic AI solutions, visit clarivate.com/ai/academia.
10.1146/katina-110424-1
