The Association of College and Research Libraries (ACRL) recently published AI Competencies for Academic Library Workers, a framework for developing AI literacy across library roles. While this document primarily focuses on academic libraries, I believe it is a valuable resource for all librarians. The competencies may fit well within your context or provide a good place to begin discussions about what AI competencies are needed in your area.
AI Competencies for Academic Library Workers
ACRL’s document includes four overarching AI competencies:
- Ethical Considerations
- Knowledge and Understanding
- Analysis and Evaluation
- Use and Application
Below is an overview of each one, followed by examples of how the framework can translate across different library contexts.
1. Ethical Considerations
Acknowledging that AI is transforming many aspects of librarianship, ACRL positions ethics as the foundation for making decisions about AI use in libraries.
“Library workers must be aware of the broad range of ethical issues connected with the exploration, evaluation, selection, use, and creation of AI tools. These issues include data sources and use, the designs of algorithms and models, and societal and environmental impacts.”
Ethical considerations influence how you engage with AI and apply the other competencies outlined in the framework. This competency is about building repeatable habits for identifying risk, questioning assumptions, and setting guardrails around AI use in the library.
2. Knowledge and Understanding
“These competencies provide a foundation for developing a basic understanding of artificial intelligence technologies.”
In ACRL’s framing, foundational knowledge enables library workers to participate credibly in AI-related decisions. This applies internally (e.g., developing policy and training staff) as well as externally (e.g., user guidance on AI tools).
“Having this understanding will help library workers influence how AI is developed and implemented in academic libraries. It also lays the groundwork for other AI competencies in this document.”
3. Analysis and Evaluation
“These competencies position library workers to evaluate and analyze artificial intelligence tools effectively, bridging the gap between understanding AI and implementing or creating new AI tools.”
The framework asserts that librarians need to be well-versed in AI tools to assess the role of AI within the library. This includes evaluating how tools can be implemented responsibly to improve access to resources, support collections management, and streamline administrative work.
“Librarians must evaluate AI tools’ reliability, performance, and effectiveness while being mindful of ethical considerations to prevent misuse and misapplication.”
4. Use and Application
“Use of AI should be critically evaluated based on context, appropriateness, and alignment with library values. Adoption of AI technologies is neither necessary nor beneficial in all cases.”
The competencies outlined under Use & Application focus on applying AI deliberately—and only when it is appropriate to do so—across library workflows. The framework highlights the need for “context-aware and iterative prompting” to ensure outputs are helpful, relevant, and effective.
“Prioritizing usability and accessibility when choosing which tools to use enables everyone to benefit from AI.”
How to Apply These Core Competencies in Library Practice
Each overarching competency has sub-competencies that provide more granular guidance for developing AI literacy. These sub-competencies break down the broader categories into actionable skills and knowledge areas that library workers can progressively develop.
Whether you work in a school library or a special library, these overarching competencies remain essential foundations for navigating AI in library practice. The specific ways the competencies manifest will then be tailored to your context.
AI Competencies for School Librarians
A school librarian might apply ethical considerations when selecting AI-powered reading recommendation tools for students of varying ages, ensuring that the content and data privacy protections are age-appropriate.
AI Competencies for Special Librarians
In contrast, a special librarian might focus on evaluating AI research tools for competitive intelligence gathering while maintaining confidentiality and intellectual property standards.
AI Competencies for Law Librarians
A law librarian might need deeper technical knowledge of how AI tools used in legal research handle citations, jurisdictional differences, and privacy.
The Need for AI Literacy Transcends Library Type
What is nice about this framework is its flexibility: the core competencies transcend library type. I encourage you to explore the document and decide how to apply it in your context.
0 Comments