As of August 2026, Librarian has an AI-exposure score of 56/100 (Elevated exposure) on the AI-Safe Careers index. This is an estimate of task exposure, not a prediction of job loss.
Score inputs for this role: AI-Safe Careers curated modeled estimate. This curated role has no matched O*NET SOC or empirical occupation signal. Treat it as a lower-confidence directional estimate. BLS labor-market figures are separate context, not score inputs.

AI Exposure Score for

Librarian

56/100
Elevated exposure
LowModerateElevatedHighVery High

More exposed than 50% of the roles we track. Median pay ~US$61,000.

Pay & demand figures are US medians (in USD; curated approximation (not refreshed from BLS; 2022–32 framing)) - your local figures will differ. Your exposure score applies broadly.

Will AI replace Librarian?

No exposure score can predict whether AI will replace this role. The 56/100 score means our current model estimates elevated task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.

Early-career context (study ages 22-25)

This role is in the Elevated exposure band, but its assessed task mix is not automation-heavy. The study found the decline concentrated where AI was more likely to automate rather than augment work, so the headline figure should not be applied directly.

The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.

Use the task map to identify durable work and the skills worth building early.

Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision

This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.

Data sources, not endorsements: O*NET and curated role data; empirical AI signals where matched; BLS employment, pay, and demand as separate context.Methodology Data sources
Role snapshot

What this role usually involves

O*NET 29.1 title match

Administer and maintain libraries or collections of information, for public or private access through reference or borrowing. Work in a variety of settings, such as educational institutions, museums, and corporations, and with various types of informational materials, such as books, periodicals, recordings, films, and databases. Tasks may include acquiring, cataloging, and circulating library materials, and user services such as locating and organizing information, providing instruction on how to access information, and setting up and operating a library's media equipment.

Common titles
LibrarianLibrary Media SpecialistMedia SpecialistReference LibrarianCatalog LibrarianInstructional Technology Specialist
O*NET job-zone preparation
Job Zone 5 · Extensive Preparation Needed Most of these occupations require graduate school. For example, they may require a master's degree, and some require a Ph.D., M.D., or J.D. (law degree). Extensive skill, knowledge, and experience are needed for these occupations. Many require more than five years of experience.

Broad guidance for this preparation level; exact requirements vary by role and employer.

Skills and knowledge
Information scienceResearchCustomer and Personal ServiceEnglish LanguageComputers and ElectronicsEducation and Training
Work context
Frequent contact with othersIndoor controlled settingDecision latitude

Source: O*NET 29.1 title match - Librarians and Media Collections Specialists, SOC 25-4022.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.

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Librarian tasks, by AI exposure

Automatable
  • Catalog and manage collections
  • Code, classify, and catalog books, publications, films, audio-visual aids, and other library materials, based on subject matter or standard library classification systems.
  • Keep up-to-date records of circulation and materials, maintain inventory, and correct cataloging errors.
6 more automatable tasks locked in the report.
Augmentable
  • Help patrons find resources
  • Search standard reference materials, including online sources and the Internet, to answer patrons' reference questions.
4 more augmentable tasks locked in the report.
Durable
  • Run programs and instruction
  • Curate and advise
3 more durable tasks locked in the report.

We analyzed all 20 Librarian tasks - 9 automatable, 6 augmentable and 5 durable. The full task map - every task with exactly what to do about each - is in your Career Report.

Your report unlocks three concrete artifacts

Full task map

Every task scored with what to automate, augment, or protect.

Adjacent path comparison

Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.

30/60/90 plan + PDF

A keepable roadmap plus resume and LinkedIn repositioning.

Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.

Adjacent career paths

Relatedness shows how reachable a move may be. A path is labeled lower exposure only when its score is at least 6 points lower; every row shows the measured difference.

UX Researcher
66% skills overlap; 6 points lower - lower exposure; Elevated band; ~US$97,650
View path
50
7 more adjacent paths with exposure deltas, salary, demand, and reachability in your Career Report.
Agent Reality Check (on-site workflow preview)

Catalog and manage collections

Check what deployed AI agents can attempt on tasks like this using dated capability evidence. You review the real task before any analysis runs.
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Your AI-Safe Career Report

Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.

Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026

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Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.