Full Curriculum
18 modules across three levels - from AI basics to building your own tools. Choose your path or work through every module in order.
18 modules · ~6 hours of material · self-paced
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Modules tagged Practicing focus on reference, instruction, and research support. Modules tagged Digital focus on metadata, systems, and cataloging. All are tagged for both or one audience.
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Level 1: Foundations
Build your AI foundation: how it works, how to talk to it, which tools to use, and how to think critically about what it produces.
5/5 modules available
View level hub →What AI actually is
AI tools feel like magic until something goes wrong. Understanding how they actually work, at a nontechnical level, changes how you use them. This module gives you the mental model you need to work with AI effectively and critically.
Talking to AI effectively
Most people underuse AI because they talk to it like a search engine. This module teaches you how to actually communicate with AI, the skill that separates people who get useful results from those who don't.
Picking the right tool
There are dozens of AI tools and new ones appear weekly. This module gives you a framework for evaluating them, a practical comparison of the major tools you'll encounter, and clear guidance on when not to use AI at all.
Ethics, copyright & policy
Ethics are not separate from practical AI use; they are embedded in every decision about which tool to use, what to put into it, and what to do with what comes out. This module maps the ethical landscape you need to navigate in library work.
Critical evaluation of AI output
Librarians have been teaching critical evaluation of sources for decades. AI does not require a new framework; it requires applying what you already know to a new type of source. This module bridges that connection.
Level 2: Applied
Put AI to work in real library workflows: research support, instruction, metadata, reference, and making the case to leadership.
8/8 modules available
View level hub →AI for research support
Research support is where many librarians first encounter real AI utility, and real AI failure. This module maps where AI adds value to literature reviews, search strategy, and evidence synthesis, and where it gets students into trouble.
Reference & instruction
Reference and instruction are where librarians spend the most time, and where AI provides the most immediate daily utility. This module is entirely practical: real tasks, real prompts, real time savings.
Metadata & cataloging
Metadata work is labor intensive, detail oriented, and increasingly supported by AI tools. This module covers the real state of AI in cataloging: where it saves hours, where it introduces errors, and how to design quality controlled workflows.
Digital collections & discovery
AI is reshaping how patrons discover library collections, and how libraries describe them. This module covers the practical state of AI in discovery layers, digital collections, and institutional repositories.
Prompt library for library work
The difference between occasional AI users and power users is a prompt library. This module teaches you to build one, systematically capturing what works so you don't start from scratch every time.
AI for collections & vendor evaluation
Vendors are selling academic libraries AI products faster than libraries can evaluate them. This module covers where AI actually fits in collection development and acquisitions, how to test vendor AI search tools against your own queries, and how to decide what is worth the budget.
Making the case to administration
You've tried AI, you've seen the value, and now you need to bring your institution along. This module covers the practical advocacy work: how to frame the case, what data to use, and how to run a pilot that builds institutional confidence.
AI, labor & the library worker
Every AI adoption decision is also a labor decision. This module covers ALA's Labor value: why AI must not justify job cuts or deskilling, how to build genuine worker input into AI decisions, the hidden human labor behind the tools, and how to turn efficiency gains into better working conditions rather than fewer positions.
Level 3: Advanced
★ First in fieldBuild, automate, and integrate: the modules no one else is teaching. Vibe coding, agentic AI, workflow automation, and systems integration.
5/5 modules available
View level hub →Automating repetitive tasks
The first library automation course designed for nonprogrammers. You'll learn to identify what's worth automating, build your first real automations using visual tools, and see concrete time savings in your actual workflow.
Agentic AI: what it means
AI agents take actions rather than just answering questions. Understanding what they are, and what library workflows they could handle, is the next frontier for digital librarians.
Vibe coding for librarians
The first practitioner focused vibe coding curriculum for librarians. No programming required. You will describe what you want in plain language and watch it become a working tool. We will build real library tools together, and we will also reckon honestly with the risks.
AI & library systems integration
For digital librarians ready to connect AI to the systems they manage (ILS, repositories, discovery layers) without a computer science degree. This module demystifies APIs and shows you what's actually possible.
Your AI strategy & next steps
Completing this curriculum is a beginning. This module helps you build the ongoing practice, community, and professional presence that turns a learning journey into a professional identity.
All modules are mapped to the ACRL AI Competencies for Academic Library Workers (October 2025) at the sub-competency level.
Modules and content are subject to change and ongoing updates as the AI landscape evolves.