Occupation · SOC 25-4031.00
Assist librarians by helping readers in the use of library catalogs, databases, and indexes to locate books and other materials; and by answering questions that require only brief consultation of standard reference. Compile records; sort and shelve books or other media; remove or repair damaged books or other media; register patrons; and check materials in and out of the circulation process. Replace materials in shelving area (stacks) or files. Includes bookmobile drivers who assist with providing services in mobile libraries.
Also called: Library Assistant · Library Associate · Library Technical Assistant (LTA) · Library Technician · Circulation Clerk · Library Aide · Library Clerk · Library Media Technician · Library Specialist · Page Technician · Accessioner · Audio-Visual Aide
Job family: Educational Instruction and Library Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-25-4031-00/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
62nd-percentile task overlap — yet about 13,000 openings a year (-6.8% projected, BLS), and observed AI use leans 3695% copilot, not hand-off (AEI) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Moderate | 49th | 0.0 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 59th | 0.8 | |
| AI assistant applicability (Microsoft) High | 82nd | 0.3 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.4), with simple added tooling (β 0.6), and including AI-powered software (γ 0.8). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 1.0 · 99th percentile among occupations · High
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Compose explanatory summaries of contents of books and other reference materials. | 10.9% | |
| Conduct reference searches, using printed materials and in-house and online databases. | 5.1% | |
| Compile bibliographies and prepare abstracts on subjects of interest to particular organizations or groups. | 2.5% | |
| Help patrons find and use library resources, such as reference materials, audio-visual equipment, computers, and other electronic resources and provide technical assistance when needed. | 2.0% | |
| Retrieve information from central databases for storage in a library's computer. | 2.0% | |
| Organize and maintain periodicals and reference materials. | 0.5% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -6.8% by 2034 |
| Projected annual openings | 13,000 |
| Employment 2024 → 2034 | 78,600 → 73,200 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international 2 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Library Clerks · 4411 | 46% | Gradient 2 |
| Gallery, Museum and Library Technicians · 3433 | 37% | Gradient 1 |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 37.0% working with AI · 53.7% handed to AI |
| Most common way people use AI here | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 3.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 33.3% |
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Retrieve information from central databases for storage in a library's computer. | Directive | 2.4% |
| Compile bibliographies and prepare abstracts on subjects of interest to particular organizations or groups. | Directive | 2.2% |
| Conduct reference searches, using printed materials and in-house and online databases. | Directive | 2.0% |
| Compose explanatory summaries of contents of books and other reference materials. | Directive | 0.9% |
| Help patrons find and use library resources, such as reference materials, audio-visual equipment, computers, and other electronic resources and provide technical assistance when needed. | Directive | 0.7% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Conduct reference searches, using printed materials and in-house and online databases. | 100.0% | |
| Compose explanatory summaries of contents of books and other reference materials. | 98.8% | |
| Compile bibliographies and prepare abstracts on subjects of interest to particular organizations or groups. | 98.2% | |
| Help patrons find and use library resources, such as reference materials, audio-visual equipment, computers, and other electronic resources and provide technical assistance when needed. | 97.1% | |
| Retrieve information from central databases for storage in a library's computer. | 93.4% |
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
Help me retrieve information from central databases for storage in a library's computer. From: Retrieve information from central databases for storage in a library's computer. · 2.4% of measured AI use · directive
Help me compile bibliographies and prepare abstracts on subjects of interest to particular organizations or groups. From: Compile bibliographies and prepare abstracts on subjects of interest to particular organizations or groups. · 2.2% of measured AI use · directive
Help me conduct reference searches, using printed materials and in-house and online databases. From: Conduct reference searches, using printed materials and in-house and online databases. · 2.0% of measured AI use · directive
Help me compose explanatory summaries of contents of books and other reference materials. From: Compose explanatory summaries of contents of books and other reference materials. · 0.9% of measured AI use · directive
All 35 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
Newer responsibilities O*NET has flagged as growing for this occupation.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Customer and Personal Service | 4.1 | |
| English Language | 3.8 | |
| Administrative | 3.4 | |
| Computers and Electronics | 3.3 | |
| Education and Training | 3.2 | |
| Communications and Media | 2.8 | |
| Psychology | 2.6 | |
| Mathematics | 2.6 |
| Reading Comprehension | 3.4 | |
| Active Listening | 3.3 | |
| Speaking | 3.3 | |
| Critical Thinking | 3.0 | |
| Learning Strategies | 3.0 | |
| Writing | 2.9 | |
| Active Learning | 2.9 | |
| Monitoring | 2.9 |
| Oral Comprehension | 3.4 | |
| Oral Expression | 3.4 | |
| Written Comprehension | 3.3 | |
| Near Vision | 3.3 | |
| Speech Recognition | 3.3 | |
| Speech Clarity | 3.3 | |
| Category Flexibility | 3.1 | |
| Written Expression | 3.0 | |
| Deductive Reasoning | 3.0 | |
| Information Ordering | 3.0 | |
| Far Vision | 3.0 | |
| Problem Sensitivity | 2.9 | |
| Inductive Reasoning | 2.9 | |
| Flexibility of Closure | 2.9 | |
| Selective Attention | 2.9 | |
| Finger Dexterity | 2.9 | |
| Perceptual Speed | 2.8 |
| Service Orientation | 3.1 | |
| Social Perceptiveness | 3.0 | |
| Coordination | 3.0 | |
| Judgment and Decision Making | 2.9 | |
| Time Management | 2.8 | |
| Management of Personnel Resources | 2.8 | |
| Instructing | 2.6 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 47.
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Library Science . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Bachelor's Degree | 29.6% | |
| Associate's Degree (or other 2-year degree) | 27.7% | |
| Post-Secondary Certificate | 17.1% | |
| High School Diploma | 15.0% | |
| Some College Courses | 8.8% | |
| Master's Degree | 1.8% |
The interests and personal qualities O*NET associates with people who do this work.
| Conventional | 6.5 | |
| Social | 4.1 | |
| Realistic | 3.1 | |
| Investigative | 2.7 |
| Office Work | 4.9 | |
| Personal Service | 3.2 | |
| Teaching/Education | 2.5 | |
| Humanities | 2.5 | |
| Information Technology | 2.2 | |
| Physical/Manual Labor | 2.2 | |
| Social Service | 2.0 | |
| Management/Administration | 1.9 | |
| Human Resources | 1.9 |
| Dependability | 3.0 | |
| Cooperation | 2.3 | |
| Attention to Detail | 2.3 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $27,890 |
| 25th percentile | $33,510 |
| Median (50th) | $39,970 |
| 75th percentile | $49,740 |
| 90th percentile | $60,960 |
| People employed | 73,770 |
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Educational Services · Sector | 24,180 | $45,800 |
| Information · Sector | 4,550 | $42,320 |
| Other Services (except Public Administration) · Sector | 190 | $47,660 |
| Arts, Entertainment, and Recreation · Sector | 130 | $43,200 |
| Health Care and Social Assistance · Sector | 110 | $50,140 |
| Professional, Scientific, and Technical Services · Sector | — | $35,860 |
| Administrative and Support and Waste Management and Remediation Services · Sector | — | $42,940 |
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Educational Services · Sector | 3.7× | 24,180 |
| Information · Sector | 3.27× | 4,550 |
| Arts, Entertainment, and Recreation · Sector | 0.1× | 130 |
| Other Services (except Public Administration) · Sector | 0.09× | 190 |
| Health Care and Social Assistance · Sector | 0.01× | 110 |
Part of the Education career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Library Technicians — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 77th percentile of 427 international occupations.
Library Technicians show 62nd-percentile AI task overlap — and about 13,000 annual U.S. openings
Library Technicians show 62nd-percentile AI task overlap — and about 13,000 annual U.S. openings • Library Technicians rank in the 62nd percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 13,000 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be declining (-6.8%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $39,970, across about 73,770 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 37% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Library Technicians". https://singulariki.com/roles/role-25-4031-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
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Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Library Technicians." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-25-4031-00
Singulariki. (2026). Library Technicians. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-25-4031-00
@misc{singulariki-role-25-4031-00,
title = {Library Technicians},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-25-4031-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.