AI literacy in academic libraries: Emerging perspectives from the community
As AI adoption in academia continues to shape how knowledge is accessed and evaluated, libraries are emerging as pivotal partners in navigating this change responsibly. Building AI literacy by understanding how AI-powered research tools work, including their limitations and their ethical implications, has become an essential component of information literacy. To help address this need, Clarivate has partnered with Choice and ACRL to launch the free AI Literacy Microcourse, developed by librarians for librarians.
The course comprises eight weeks of concise, self-paced modules aligned with the ACRL AI Literacy Framework. Core AI literacy concepts are explored through readings, multimedia content, case studies, and interviews with thought leaders from across the academic field. More than 8,000 participants have registered since it launched this summer. The course remains freely available to the library community over the next few months.
Insights from the academic library community
Each lesson sparked active online discussions, generating dozens to hundreds of comments each week. Taken together, this collective dialogue offers valuable insight into how librarians are thinking about AI, what excites them, where they see opportunity, and what challenges continue to hinder adoption.
Ten key themes emerged from the conversations:
- Libraries as AI literacy leaders
Librarians see a clear role for themselves as campus guides, helping students and faculty use AI responsibly, embedding it within information literacy, and establishing guardrails for ethical use.
“The library can serve as a central leader in AI adoption by creating learning hubs with workshops, tutorials, and drop-in sessions for exploring AI tools.”
- Unclear policies
Institutional policies on AI remain inconsistent. Some campuses have established guidelines, while others are still developing them. Librarians expressed a strong desire for clear, transparent, and practical policies they can reference in their work.
- Ethics and integrity
Concerns about plagiarism, bias, and privacy were recurring. The prevailing sentiment was that AI tools should not be banned but rather taught for ethical and informed use.
“I tell students that when they use generative AI, they have to always check the information generated to a trusted source… AI should enhance their thinking, not replace it.”
- Training needs
There is high demand for hands-on training for librarians themselves and for the communities they support. Participants cited the need for workshops, teaching materials, and ready-to-use resources, but noted that time and confidence remain barriers.
“We provide events and workshops, resources such as guides, FAQs and videos to support the evaluation of Gen AI usage.”
- Need for collaboration
Librarians emphasized the importance of cross-campus collaboration. Many are seeking opportunities to engage with faculty, IT, and academic leadership, as well as to learn from peers through communities of practice.
- Checking AI outputs
Verification emerged as a central theme. Students in particular struggle to recognize when AI-generated content is inaccurate or biased. Librarians underscored the importance of teaching critical evaluation and source verification.
“Students should always do cross-checks if references are provided by the tool, critically evaluate and look out for biases.”
- Evaluating AI tools
When assessing AI tools, librarians prioritize criteria such as usability, privacy, interoperability, cost, and transparency about data sources. Provenance and auditability are seen as key.
“When evaluating AI tools for our library, we focus on how well they align with academic integrity and instructional goals… reliability, accuracy, and transparency are the most important criteria.”
- Barriers and enablers
The most common barriers identified were budget constraints, limited staffing, and a lack of institutional policy. Enablers included strong governance, leadership support, and opportunities for reskilling.
- Quick wins
Participants highlighted the value of small, actionable steps such as updating AI LibGuides, drafting policy templates, hosting workshops, and partnering with vendors for pilot projects.
- Future outlook
Looking ahead, librarians expressed a mix of optimism and caution. Some view AI as a powerful assistant that can enhance learning and streamline workflows, while others raise concerns about job displacement, workload pressures, and over-reliance on automation. Interest in emerging technologies, such as agentic AI, is growing steadily.
The discussions surrounding the AI Literacy Microcourse reaffirm a key message: librarians want to play an active role in shaping how AI is understood and used in academia. To do so effectively, they need clarity, training, and institutional support. Notably, many of these same themes surfaced in the recent Pulse of the Library survey conducted by Clarivate, which provided a quantitative perspective on AI adoption across the library community.
Take the AI Literacy Essentials for Academic Libraries Microcourse today.
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