
AI+ Librarians
Curate, Discover and Serve Smarter with AI
AI for the profession that verifies before it trusts.
Your cataloguing backlog is growing, patrons are bringing AI-generated citations to verify, and everyone is asking you whether AI can be trusted — before you've formed a considered answer yourself. This book gives librarians the Librarian AI Safety Protocol, the Librarian Prompt Toolkit (28 copy-ready prompts across Curate–Discover–Serve), and practical guidance that upholds patron privacy and collection authority. Written for information professionals by an AI engineering firm.
AI+ CoursesRelated Courses
AI+ Librarians — Video Course
This book is also a self-paced video course. Tap any module to preview.
- 28 ready-made, market-tested prompts: cataloguing, metadata, reference, research support, patron communications, IL instruction
- The Librarian AI Safety Protocol — six-check framework for patron privacy, intellectual freedom, authority, copyright, collection integrity, professional compliance
- The Citation Verification Loop — a three-step discipline applied to every AI-surfaced source before it reaches a patron
- Sector-specific routing for academic, public, school, special, and national library settings — your context recognised
- A 30-day plan structured around the Curate–Discover–Serve cycle that unites every library sector
Any professional whose primary role involves curating, organising, and providing access to information and knowledge resources. This includes: academic and university librarians, public librarians, school and college librarians, special librarians (law, medical, corporate, government), national library and archive staff, research and subject librarians, cataloguers and metadata specialists, and information literacy instructors. Typically MLIS/MLS qualified or equivalent, 3–25+ years in the profession. The common thread: they help communities — students, researchers, professionals, the general public — find, evaluate, and use trustworthy information. Their daily work involves a recurring cycle of curating collections, supporting discovery, and serving patrons.
Also for:Library assistants and paraprofessionals taking on expanded duties; library directors and heads of service wanting a practical foundation before making strategic decisions; archivists and records managers; information architects in adjacent roles; LIS students preparing for the profession; educators working closely with their library (see T2-80).
- Identify at least five areas in their daily library work (collection curation, cataloguing and metadata, reference and research support, patron services, and information literacy instruction) where AI can improve quality or efficiency
- Apply structured prompting techniques (PRISM) to core library tasks: drafting catalogue records and metadata, producing reference answers and literature scans, writing patron-facing communications, and summarising policy or research material
- Evaluate AI-generated information using the TRUST framework with librarian-specific criteria — authority, provenance, currency, bias, and accuracy — at the professional standard expected of an information specialist
- Apply the Librarian AI Safety Protocol to protect patron privacy, uphold intellectual freedom, respect copyright and licensing, and maintain the authority of the collection
- Design a personal 30-day AI adoption plan mapped to the Curate–Discover–Serve cycle and demonstrate measurable improvement in at least three routine library tasks
- Diagnostic
- How AI-Ready Is Your Library Practice?
- Chapter 1
- AI in Libraries Right Now
- Chapter 2
- What AI Can (and Cannot) Do for Librarians
- Chapter 3
- How to Prompt AI as a Librarian
- Chapter 4
- AI for Curation
- Chapter 5
- AI for Discovery
- Chapter 6
- AI for Service
- Chapter 7
- AI Safety, Privacy and Professional Ethics
- Chapter 8
- AI, Information Literacy and the Librarian as Educator
- Chapter 9
- AI Across Library Sectors
- Chapter 10
- Your 30-Day Librarian AI Starter Plan
- Back matter
- Skill Summary · Recommended Next Reads · Glossary · Tool Reference
Built by an AI engineering firm — for the profession that holds the line on what trustworthy information looks like.
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