Police and Sheriff's Patrol Officers
In short: today's best AI models could do about 13% 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 14% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 86% of the time, stays with people.
Maintain order and protect life and property by enforcing local, tribal, state, or federal laws and ordinances. Perform a combination of the following duties: patrol a specific area; direct traffic; issue traffic summonses; investigate accidents; apprehend and arrest suspects, or serve legal processes of courts. Includes police officers working at educational institutions.
670,520 people do this job in the US. $76,210 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 on0 h
- A person checks AI's work5 h
- Desk work AI can't do yet1 h
- Stays with people34 h
Police and Sheriff's Patrol Officers, now: of a 40-hour week, AI could take on 0 hours, 5 hours become checking its work, 1 hours are desk work it can't do yet, and 34 hours stay with people.
The largest pieces: Write incident reports (about 1 h, a person checks); Supervise law enforcement staff (about 1 h, a person checks); Verify charges against offenders (under an hour, 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.
- 12%
- 2%
- 1%
- 26%
- 58%
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 13% 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, 0%. With Claude Mythos Preview (early), measured in April 2026, 9%. Today's estimate: 13%.
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, 0.011% went to this job's tasks in May 2026, the 398th largest of the 447 jobs that showed up at all; 1 of its 30 tasks showed up. Within each of Anthropic's methods, never across a change: 0.079% to 0.063% (released February and March 2025); 0.036% to 0.028% (August 2025 to February 2026); 0.011% to 0.011% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.079% | 203 of 708 | 5 of 30 |
| Released March 2025 | 0.063% | 231 of 703 | 3 of 30 |
| The week of Aug 4, 2025 (released September 2025) | 0.036% | 282 of 655 | 2 of 30 |
| The week of Nov 13, 2025 (released January 2026) | 0.018% | 400 of 672 | 2 of 30 |
| The week of Feb 5, 2026 (released March 2026) | 0.028% | 352 of 677 | 2 of 30 |
| April 2026 (released June 2026) | 0.011% | 382 of 434 | 1 of 30 |
| May 2026 (released June 2026) | 0.011% | 398 of 447 | 1 of 30 |
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 66% of this job's working time as physical work. For 7% of the working time, a robot has been shown doing most of the task somewhere: 1% in a purpose-built cell, 6% in a structured facility. 0.13 of 3, the 496th highest of the 923 jobs.
- Not physical 34%
- No robot shown 59%
- In a purpose-built cell 1%
- In a structured facility 6%
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
83% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Patrol by vehicle, cite and arrest, the hands-on work, 12%
- Keep order and respond to emergencies, the hands-on work, 11%
- Pursue and arrest suspects, the hands-on work, 10%
- Investigate suspicious activities, the hands-on work, 9%
- Patrol an assigned area, the hands-on work, 9%
- Supervise law enforcement staff, the in-person work, 7%
What becomes checking the machine
14% 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.
- Write incident reports, severe if wrong, 3%
- Supervise law enforcement staff, a licensed person signs, 3%
- Investigate suspicious activities, a licensed person signs, 2%
- Verify charges against offenders, a licensed person signs, 2%
- Review incidents for criminal violations, a licensed person signs, 2%
- Investigate accidents, a licensed person signs, 0.7%
What to learn
- Signing off under your license. Some tasks need a licensed, certified or sworn person to do or sign them. The license, and the judgment it stands for, stays with the person.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- The hands-on craft. About 58% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
- The conversations. About 27% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
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 . 30 tasks from .
| Task | ||||
|---|---|---|---|---|
| Drive vehicles or patrol specific areas to detect law violators, issue citations, and make arrests.Driving a beat, with stops made in person.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 12% | 1.7 h25 min to 3.3 h | Hands-on 80%, in person 20% | Stays with people |
| Investigate illegal or suspicious activities.Looking, asking and following up in person, with notes written.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 12% | 2.5 h25 min to 1.3 work days | Hands-on 50%, in person 30%, documents 20% | 13%Desk part half by now |
| Provide for public safety by maintaining order, responding to emergencies, protecting people and property, enforcing motor vehicle and criminal laws, and promoting good community relations.Being there: on the street, at the scene, among people.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 11% | 1.7 h25 min to 6.7 h | Hands-on 60%, in person 40% | Stays with people |
| Identify, pursue, and arrest suspects and perpetrators of criminal acts.Chasing and taking people into custody.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 10% | 2.5 h38 min to 6.7 h | Hands-on 80%, in person 20% | Stays with people |
| Supervise law enforcement staff, such as jail staff, officers, and deputy sheriffs.Leading officers in person, with reports reviewed.Done hourly or more by most who do it. | 9% | 3.3 h50 min to 6.7 h | In person 70%, documents 30% | 27%Desk part half by now |
| Patrol specific area on foot, horseback, or motorized conveyance, responding promptly to calls for assistance.On foot or in a vehicle, answering calls.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 1.7 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Patrol and guard courthouses, grand jury rooms, or assigned areas to provide security, enforce laws, maintain order, and arrest violators.Standing guard, with a word to those who come and go.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 1.7 h50 min to 6.7 h | Hands-on 80%, in person 20% | Stays with people |
| Monitor traffic to ensure motorists observe traffic regulations and exhibit safe driving procedures.Watching the road from a patrol car.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Investigate traffic accidents and other accidents to determine causes and to determine if a crime has been committed.Examining the scene, questioning those involved, and writing it up.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 1.7 h25 min to 3.3 h | Hands-on 50%, in person 30%, documents 20% | 20%Desk part half by now |
| Record facts to prepare reports that document incidents and activities.A written report, filed in the records system.Done daily by most who do it. AI observed on this task. | 3% | 38 min17 min to 1.7 h | Documents 70%, systems 30% | 100%Half by now |
| Monitor, note, report, and investigate suspicious persons and situations, safety hazards, and unusual or illegal activity in patrol area.Being out on patrol, looking and stopping to ask.Done daily by most who do it. Robots: in a structured facility, Knightscope K5 Autonomous Security Robot (Knightscope, Inc.) (deployed). Anthropic's rating. | 3% | 38 min13 min to 2.5 h | Hands-on 70%, in person 30% | Stays with people |
| Verify that the proper legal charges have been made against law offenders.Reading the charges against the facts and the statute, in the records.Done daily by most who do it. | 2% | 38 min13 min to 1.7 h | Documents 70%, systems 30% | 100%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.
- Detectives and Criminal Investigators69% now, 74% by 2028
- First-Line Supervisors of Police and Detectives44% now, 53% by 2028
- Transit and Railroad Police21% now, 32% by 2028
- Bailiffs9% now, 9% by 2028
- Private Detectives and Investigators33% now, 69% by 2028
- Probation Officers and Correctional Treatment Specialists34% now, 37% 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 Police and Sheriff's Patrol Officers is within reach of AI now?
- An estimated 13% of the working time is within reach of AI models now and 14% 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 Police and Sheriff's Patrol Officers 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: Write incident reports (100% of the task's time now); Supervise law enforcement staff (27% of the task's time now); and Verify charges against offenders (100% of the task's time now).
- Which tasks of Police and Sheriff's Patrol Officers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Patrol by vehicle, cite and arrest; Keep order and respond to emergencies; and Pursue and arrest suspects. Together such tasks are about 65% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Police and Sheriff's Patrol Officers learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are signing off under your license; judgment where errors are severe; and the hands-on craft. By the end of 2028 on the long-run pace at four in five, about 83% of the working time stays with people, 14% becomes checking a model's work and 0% 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 Police and Sheriff's Patrol Officers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.011% went to this job's tasks, the 398th largest share of the 447 jobs that showed up; 1 of its 30 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 12%. 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 Police and Sheriff's Patrol Officers?
- Anthropic's robot exposure rating (September 2026) finds 66% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 7% of the working time, 6% in a structured facility. Its index is 0.13 of 3. One example: Knightscope K5 Autonomous Security Robot for "watch for and investigate suspicious activity". 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 30 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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