Library Technicians
In short: today's best AI models could do about 47% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 53% of the time, stays with people.
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.
68,690 people do this job in the US. $44,580 a year.
Reviewed on October 2, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on17 h
- A person checks AI's work2 h
- Desk work AI can't do yet0 h
- Stays with people21 h
Library Technicians, now: of a 40-hour week, AI could take on 17 hours, 2 hours become checking its work, 0 hours are desk work it can't do yet, and 21 hours stay with people.
The largest pieces: Keep circulation records (about 3 h); Report library usage statistics (about 3 h); Write book summaries (about 2 h).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 21%
- 25%
- 1%
- 24%
- 28%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 47% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 3%. With Claude Mythos Preview (early), measured in April 2026, 39%. Today's estimate: 47%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 1.6% went to this job's tasks in May 2026, the 14th largest of the 447 jobs that showed up at all; 3 of its 31 tasks showed up. Within each of Anthropic's methods, never across a change: 0.09% to 0.25% (released February and March 2025); 0.14% to 0.086% (August 2025 to February 2026); 1.6% to 1.6% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.09% | 182 of 708 | 9 of 31 |
| Released March 2025 | 0.25% | 80 of 703 | 10 of 31 |
| The week of Aug 4, 2025 (released September 2025) | 0.14% | 128 of 655 | 5 of 31 |
| The week of Nov 13, 2025 (released January 2026) | 0.092% | 166 of 672 | 7 of 31 |
| The week of Feb 5, 2026 (released March 2026) | 0.086% | 181 of 677 | 7 of 31 |
| April 2026 (released June 2026) | 1.6% | 14 of 434 | 3 of 31 |
| May 2026 (released June 2026) | 1.6% | 14 of 447 | 3 of 31 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 51% of this job's working time as physical work. For 47% of the working time, a robot has been shown doing most of the task somewhere: 47% in a purpose-built cell. 0.47 of 3, the 321st highest of the 923 jobs.
- Not physical 49%
- No robot shown 4%
- In a purpose-built cell 47%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
53% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Move items around the library, the hands-on work, 6%
- Run library programs, the in-person work, 6%
- Help patrons use resources, the in-person work, 5%
- Keep periodicals in order, the hands-on work, 4%
- Sort and shelve materials, the hands-on work, 4%
- Train and schedule helpers, the in-person work, 4%
What becomes checking the machine
4% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 43% is desk work that is small if wrong, which can be handed over with lighter checks.
- Run library programs, costly if wrong, 2%
- Order materials and pay for them, costly if wrong, 1%
What to learn
- The hands-on craft. About 28% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Running AI inside the business systems. About 25% of the time is work inside business systems, which a model can do only once it is connected: knowing the systems well enough to set that up and watch it.
- The conversations. About 25% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Briefing a model and checking its drafts. About 21% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 31 tasks from .
| Task | ||||
|---|---|---|---|---|
| Plan and conduct children's programs, community outreach programs, and other specialized programs, such as library tours.Planning the program and running it with the children or the group in the room.Done more than weekly by most who do it. | 8% | 2.5 h50 min to 5 h | In person 70%, documents 30% | 30%Desk part half by now |
| Compile and maintain records relating to circulation, materials, and equipment.Records of loans, items and equipment kept in the system.Done more than monthly by most who do it. | 7% | 38 min13 min to 1.7 h | Systems 80%, documents 20% | 100%Half by now |
| Compile data and create statistical reports on library usage.Pulling the counts from the system and writing the report.Done more than monthly by most who do it. | 6% | 1.7 h50 min to 3.3 h | Documents 70%, systems 30% | 100%Half by now |
| Deliver and retrieve items throughout the library by hand or using pushcart.Carting items between the desk, the stacks and the rooms.Done daily by most who do it. Robots: in a purpose-built cell, Aethon TUG (T3) (deployed). Anthropic's rating. | 6% | 17 min8 min to 33 min | Hands-on 100% | Stays with people |
| Catalogue and sort books and other print and non-print materials according to procedure and return them to shelves, files, or other designated storage areas.Sorting the carts and shelving, with the catalog entries.Done daily by most who do it. Robots: in a purpose-built cell, Tech Logic totalAMH central sorter (deployed). Anthropic's rating. | 6% | 13 min4 min to 33 min | Hands-on 70%, systems 30% | 30%Desk part half by now |
| Train other staff, volunteers, or student assistants and schedule and supervise their work.Showing volunteers and assistants the work in person, with the schedule in the system.Done more than monthly by most who do it. | 6% | 50 min25 min to 2.5 h | In person 70%, systems 30% | 30%Desk part half by now |
| 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.Face to face with patrons at the shelves and the computers.Done several times a day by most who do it. | 5% | 13 min4 min to 25 min | In person 100% | Stays with people |
| Provide assistance to teachers and students by locating materials and helping to complete special projects.Finding materials with them and helping with projects, mostly in person.Done more than monthly by most who do it. | 5% | 33 min13 min to 1.3 h | In person 70%, documents 30% | 30%Desk part half by now |
| Compose explanatory summaries of contents of books and other reference materials.Reading and writing short summaries.Done more than yearly by most who do it. AI observed on this task. | 5% | 1.7 h38 min to 4.2 h | Documents 100% | 100%Half by now |
| Organize and maintain periodicals and reference materials.Shelving and tidying the periodicals and reference shelves.Done more than weekly by most who do it.Robots: in a purpose-built cell, Oodi Library automated return, sorting and shelving system (sorter + Universal Robots UR10 + Robotiq 2F-85 gripper + MiR AMRs) (Mikro-Vayla Oy / Universal Robots / Mobile Industrial Robots, for Helsinki City Library Oodi) (deployed). Anthropic's rating. | 4% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Maintain and troubleshoot problems with library equipment, including computers, photocopiers, and audio-visual equipment.Hands on the copiers, computers and projectors when they fail.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 25 min8 min to 1.7 h | Hands-on 100% | Stays with people |
| Check for damaged library materials, such as books or audio-visual equipment, and provide replacements or make repairs.Looking items over, mending them, and ordering replacements.Done more than weekly by most who do it. Robots: in a purpose-built cell, BookGuard finished book quality inspection system (SINOMV) (sold). Anthropic's rating. | 4% | 21 min8 min to 50 min | Hands-on 80%, systems 20% | 20%Desk part half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Library Assistants, Clerical35% now, 36% by 2028
- File Clerks50% now, 53% by 2028
- Office Clerks, General56% now, 56% by 2028
- Document Management Specialists70% now, 93% by 2028
- Secretaries and Administrative Assistants, Except Legal, Medical, and Executive59% now, 68% by 2028
- Stockers and Order Fillers19% now, 19% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Library Technicians is within reach of AI now?
- An estimated 47% of the working time is within reach of AI models now and 47% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Library Technicians come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Keep circulation records (100% of the task's time now); Report library usage statistics (100% of the task's time now); and Write book summaries (100% of the task's time now).
- Which tasks of Library Technicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Move items around the library; Help patrons use resources; and Keep periodicals in order. Together such tasks are about 27% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Library Technicians learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft; running AI inside the business systems; and the conversations. By the end of 2028 on the long-run pace at four in five, about 53% of the working time stays with people, 4% becomes checking a model's work and 43% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Library Technicians?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 1.6% went to this job's tasks, the 14th largest share of the 447 jobs that showed up; 3 of its 31 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 5%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Library Technicians?
- Anthropic's robot exposure rating (September 2026) finds 51% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 47% of the working time. Its index is 0.47 of 3. One example: Aethon TUG (T3) for "move items around the library". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 31 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on October 2, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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