Court, Municipal, and License Clerks
In short: today's best AI models could do about 75% 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 85% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 15% of the time, stays with people.
Perform clerical duties for courts of law, municipalities, or governmental licensing agencies and bureaus. May prepare docket of cases to be called; secure information for judges and court; prepare draft agendas or bylaws for town or city council; answer official correspondence; keep fiscal records and accounts; issue licenses or permits; and record data, administer tests, or collect fees.
179,750 people do this job in the US. $48,700 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on9 h
- A person checks AI's work21 h
- Desk work AI can't do yet4 h
- Stays with people6 h
Court, Municipal, and License Clerks, now: of a 40-hour week, AI could take on 9 hours, 21 hours become checking its work, 4 hours are desk work it can't do yet, and 6 hours stay with people.
The largest pieces: Direct document filing and safekeeping (about 7 h, a person checks); Maintain tracking systems (about 3 h); Keep vital and fiscal records (about 3 h, a person checks).
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.
- 38%
- 47%
- 8%
- 4%
- 2%
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 75% 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, 1%. With Claude Mythos Preview (early), measured in April 2026, 41%. Today's estimate: 75%.
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, 0.14% went to this job's tasks in May 2026, the 131st largest of the 447 jobs that showed up at all; 3 of its 29 tasks showed up. Within each of Anthropic's methods, never across a change: 0.082% to 0.066% (released February and March 2025); 0.053% to 0.058% (August 2025 to February 2026); 0.14% to 0.14% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.082% | 197 of 708 | 12 of 29 |
| Released March 2025 | 0.066% | 224 of 703 | 8 of 29 |
| The week of Aug 4, 2025 (released September 2025) | 0.053% | 237 of 655 | 7 of 29 |
| The week of Nov 13, 2025 (released January 2026) | 0.055% | 225 of 672 | 9 of 29 |
| The week of Feb 5, 2026 (released March 2026) | 0.058% | 231 of 677 | 9 of 29 |
| April 2026 (released June 2026) | 0.14% | 134 of 434 | 3 of 29 |
| May 2026 (released June 2026) | 0.14% | 131 of 447 | 3 of 29 |
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 20% of this job's working time as physical work. For 18% of the working time, a robot has been shown doing most of the task somewhere: 16% in a purpose-built cell, 3% in a structured facility. 0.21 of 3, the 430th highest of the 923 jobs.
- Not physical 80%
- No robot shown 1%
- In a purpose-built cell 16%
- In a structured facility 3%
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
14% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Answer phones, file and keep supplies, the conversation, 2%
- Answer public questions on court matters, the conversation, 2%
- Train and coordinate other clerks, the conversation, 2%
- Respond to information requests, the conversation, 2%
- Contact parties for the court, the conversation, 2%
- Take applicant details, the in-person work, 1%
What becomes checking the machine
63% 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 22% is desk work that is small if wrong, which can be handed over with lighter checks.
- Direct document filing and safekeeping, costly if wrong, 23%
- Keep vital and fiscal records, costly if wrong, 9%
- Prepare dockets, costly if wrong, 7%
- Examine filings for compliance, costly if wrong, 5%
- Assist with budgets, costly if wrong, 4%
- Prepare records of court outcomes, severe if wrong, 4%
What to learn
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Running AI inside the business systems. About 47% 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.
- Briefing a model and checking its drafts. About 38% 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.
- Handling protected records. Much of the work touches protected personal records: knowing what may be shared with a model, and how, is part of the job.
- 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 . 29 tasks from .
| Task | ||||
|---|---|---|---|---|
| Plan or direct the maintenance, filing, safekeeping, or computerization of all municipal documents.Planning how documents are filed and kept, and keeping the systems.Done daily by most who do it. | 23% | 3.3 h50 min to 1.7 work days | Documents 50%, systems 50% | 71%Half by now |
| Record and maintain all vital and fiscal records and accounts.Entries in the vital records and the accounts.Done daily by most who do it. | 9% | 2.5 h25 min to 6.7 h | Systems 100% | 79%Half by now |
| Coordinate or maintain office tracking systems for correspondence or follow-up actions.Keeping the correspondence tracking system current.Done daily by most who do it. | 8% | 1.7 h25 min to 3.3 h | Systems 100% | 99%Half by now |
| Prepare dockets or calendars of cases to be called.Building the calendar of cases in the court system.Done daily by most who do it. | 7% | 1.7 h25 min to 3.3 h | Systems 80%, documents 20% | 99%Half by now |
| Examine legal documents submitted to courts for adherence to laws or court procedures.Reading legal documents against the court's rules.Done hourly or more by most who do it. | 5% | 38 min13 min to 1.7 h | Documents 100% | 100%Half by now |
| Perform general office duties, such as taking or transcribing dictation, typing or proofreading correspondence, distributing or filing official forms, or scheduling appointments.Typing, proofreading and filing forms, and scheduling.Done hourly or more by most who do it. Robots: in a purpose-built cell, Quadient DS-180i folder inserter (sold). Anthropic's rating. | 4% | 25 min8 min to 50 min | Documents 60%, systems 40% | 100%Half by now |
| Perform budgeting duties, such as assisting in budget preparation, expenditure review, or budget administration.Budget preparation and expenditure review on paper and in the system.Done yearly or less by most who do it. | 4% | 3.3 h50 min to 1.7 work days | Documents 70%, systems 30% | 71%Half by now |
| Prepare documents recording the outcomes of court proceedings.Writing up the outcome and entering it in the record.Done hourly or more by most who do it. | 4% | 38 min13 min to 1.7 h | Documents 60%, systems 40% | 100%Half by now |
| Respond to requests for information from the public, other municipalities, state officials, or state and federal legislative offices.Written answers and calls to the public and officials.Done hourly or more by most who do it. | 3% | 25 min8 min to 50 min | Documents 50%, conversation 50% | 50%Desk part half by now |
| Perform administrative tasks, such as answering telephone calls, filing court documents, or maintaining office supplies or equipment.Calls, filing court documents and keeping the office stocked.Done hourly or more by most who do it. AI observed on this task.Robots: in a purpose-built cell, Ripcord robotic digitization workcell (sold). Anthropic's rating. | 3% | 17 min8 min to 50 min | Conversation 40%, systems 30%, hands-on 30% | 30%Desk part half by now |
| Prepare ordinances, resolutions, or proclamations so that they can be executed, recorded, archived, or distributed.Preparing the documents for signature and recording them.Done more than monthly by most who do it. | 3% | 1.7 h25 min to 3.3 h | Documents 80%, systems 20% | 99%Half by now |
| Train other workers or coordinate their work, as necessary.Day to day conversation with the desk team, with checks of their work.Done daily by most who do it. | 3% | 50 min25 min to 3.3 h | Conversation 70%, documents 30% | 30%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.
- Legal Secretaries and Administrative Assistants59% now, 60% by 2028
- Compliance Officers54% now, 67% by 2028
- Office Clerks, General56% now, 56% by 2028
- Paralegals and Legal Assistants74% now, 84% by 2028
- Title Examiners, Abstractors, and Searchers92% now, 93% by 2028
- Secretaries and Administrative Assistants, Except Legal, Medical, and Executive59% now, 68% 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 Court, Municipal, and License Clerks is within reach of AI now?
- An estimated 75% of the working time is within reach of AI models now and 86% by the end of 2028, on METR's long-run pace at four in five (85% to 86% across the three paces the site shows). 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 Court, Municipal, and License Clerks 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: Direct document filing and safekeeping (71% of the task's time now, 100% by the end of 2028); Maintain tracking systems (99% of the task's time now); and Keep vital and fiscal records (79% of the task's time now, 100% by the end of 2028).
- Which tasks of Court, Municipal, and License Clerks stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Answer public questions on court matters; Tell parties when to appear; and Explain licensing rules. Together such tasks are about 4% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Court, Municipal, and License Clerks learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are reviewing work you did not do yourself; running AI inside the business systems; and briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 14% of the working time stays with people, 63% becomes checking a model's work and 22% 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 Court, Municipal, and License Clerks?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.14% went to this job's tasks, the 131st largest share of the 447 jobs that showed up; 3 of its 29 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 10%. 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 Court, Municipal, and License Clerks?
- Anthropic's robot exposure rating (September 2026) finds 20% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 18% of the working time, 3% in a structured facility. Its index is 0.21 of 3. One example: Credential Authentication Technology (CAT-2) for "verify identity documents". 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 29 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 September 30, 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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