Police officers
Official title Police and Sheriff's Patrol Officers (SOC 33-3051)
Also called Patrol officer, Sheriff's deputy, Deputy sheriff, Law enforcement officer, Cop
In brief
In May 2025, BLS counted 670,520 US police officers, with median pay of $76,210 a year. Of the BLS counts since 2003, the May 2025 count is the highest. The earliest figure here is an estimate of 60,000 from 1900, not measured the same way as today's count. The last full technology era for police officers: Drone-as-first-responder + Clearview AI facial recognition, 2018 to 2024.
What the sources say
Official outlook
BLS projects employment to grow 3.5% from 2025 to 2035.
AI exposure studies
- 23.3% of this job's tasks are exposed to large language models. Not a forecast of job losses. Eloundou and others, 2023
- 0.098 estimated probability that the whole occupation could be computerised, over an unspecified number of years. Not a forecast of job losses. Frey and Osborne, 2013
Since the 2013 prediction
In 2013, Frey and Osborne put this job's probability of computerisation at 0.098. BLS counted 635,380 of these jobs in May 2013 and 670,520 in May 2025 (+6%, a change derived by Future History).
Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend. In May 2021 BLS changed how it estimates these counts (a model-based method using three years of survey data) and moved fully to the 2018 occupation codes, so part of a change across 2021 can come from the method rather than the work.
Last updated .
Cite this page
Future History. (2026, October 11). Police officers: jobs and pay since 1900 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/33-3051
Future History. "Police officers: jobs and pay since 1900." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/33-3051.
@misc{futurehistory_33_3051, author = {{Future History}}, title = {Police officers: jobs and pay since 1900}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/33-3051}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }
The access date is today's date on your device.
≈ $74,256 in 2024 prices (derived by us, CPI-adjusted)
May 23, 1845: New York City Mayor William Havemeyer signs the Municipal Police Act, creating the first modern municipal police department in the United States with 800 men working in round-the-clock shifts. The department is modeled on Robert Peel's London Metropolitan Police (1829): full-time paid officers in uniform, organized by precincts, under a central commissioner. Blue uniforms are introduced in 1853 after a long internal debate. The copper star badge gives officers their first lasting nickname. The NYPD founding is the institutional birth date of the American patrol officer as a professional occupation.
Berkeley, California creates the office of police chief in 1909, and August Vollmer becomes its first occupant. Over the following two decades, Vollmer builds the template for professional policing: fingerprint classification systems, forensic chemistry, handwriting analysis, the first police car radio, and, most durably, the insistence that officers must have college educations. He persuades the University of California to establish a criminal justice curriculum in 1916, headed by Vollmer himself. His reputation as 'the father of modern law enforcement' is earned from this period: he turns policing from a patronage appointment into a profession with standards, training, and a scientific basis for investigation.
The National Advisory Commission on Civil Disorders, the Kerner Commission, publishes its 426-page report in March 1968. Convened by President Johnson after the urban riots of 1967 (Detroit, Newark, and 128 other cities in a single summer), the commission's central finding is blunt: 'Our nation is moving toward two societies, one black, one white, separate and unequal.' On policing specifically, the commission documents pervasive police brutality as a precipitating factor in virtually every major riot, recommends community policing, external review boards, and the recruitment of Black officers, and warns against equipping police with mass-destruction weapons. The Kerner Report shapes the next generation of police reform discourse and directly motivates the community-policing movement of the 1980s and 1990s, even as most of its core recommendations go unimplemented.
James Q. Wilson and George Kelling publish 'Broken Windows: The Police and Neighborhood Safety' in the March 1982 issue of The Atlantic. The article argues that visible disorder (an unrepaired broken window, graffiti, litter) signals to would-be criminals that no one is watching and no one cares, which invites escalating crime. The implication for patrol: officers should prioritize order maintenance and minor-infraction enforcement alongside serious crime response. The theory becomes the intellectual foundation for the 1990s quality-of-life policing strategies in New York City under Bratton and Giuliani, and later faces serious criticism for enabling racially disparate enforcement and for contested empirical grounding.
January 1994: NYPD Commissioner William Bratton and Deputy Commissioner Jack Maple launch CompStat, COMPuter STATistics. The system compiles daily crime data by precinct onto digital maps and convenes weekly command-accountability meetings where precinct commanders must explain trends and demonstrate proactive responses. By the end of 1994, index crime in New York has fallen 12%, exceeding Bratton's public promise of 10%. CompStat spreads to virtually every major US police department within a decade, becoming the dominant management model in American policing and the first data-driven accountability system in any US government agency at scale.
August 9, 2014: Darren Wilson, a Ferguson, Missouri police officer, shoots and kills Michael Brown, an 18-year-old Black man. The shooting triggers weeks of protests, a DOJ investigation finding systemic civil-rights violations in the Ferguson PD, and a national conversation about police use of force. President Obama announces $263 million in body-camera funding in December 2014. Body-worn cameras, already available commercially but adopted by fewer than 10% of agencies, become the dominant policy response. Axon's revenues accelerate. By 2016, 47% of local general-purpose police agencies have at least some cameras deployed. Ferguson is the inflection point that transforms police technology adoption from optional to expected.
May 25, 2020: Minneapolis police officer Derek Chauvin kneels on George Floyd's neck for nine minutes and twenty-nine seconds. Floyd dies. The killing, captured on a bystander's phone video and shared globally, triggers the largest protest movement in US history. PERF's staffing surveys subsequently document a 5.5% decline in sworn officers between 2020 and 2024: resignations spike, applications plummet by approximately 40% compared to 2019, and retirements accelerate as officers eligible to leave do so. The George Floyd moment is the labor-supply inflection point in modern policing: the moment when the recruiting and retention crisis became structural rather than cyclical.
April 23, 2024: Axon announces Draft One, the first AI-powered police report-writing tool at commercial scale, using GPT-4 Turbo to transcribe body-camera audio and draft narrative incident reports in seconds. The tool requires officer review and approval before submission; it cannot be used to create a report without underlying footage. In its first months, Draft One contributes to over 100,000 incident reports and saves a documented 2.2 million officer-minutes. Departments report time savings of 50–82% on report writing: a task that historically consumes 30–40% of a patrol officer's shift. Draft One is the arrival of the LLM in the daily workflow of policing, and its primary effect is not elimination but relief: less time at a desk, more time on the street.
Will AI replace police officers? What the research says
Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.
Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.
What's changing day to day for police officers
Three parts of your work where AI is already doing real lifting, and what stays yours.
AI is sitting alongside you hereWrite incident reports documenting the facts, statements, and actions taken during each call for service, transcribing witness accounts, recording officer observations, noting elements of any offenses for legal sufficiency, and submitting the completed report through the department records management system (RMS) for supervisor review and case assignment.
Write incident reports documenting the facts, statements, and actions taken during each call for service, transcribing witness accounts, recording officer observations, noting elements of any offenses for legal sufficiency, and submitting the completed report through the department records management system (RMS) for supervisor review and case assignment.[11],[4],[7]
Report writing is the single task where AI is delivering the most measurable benefit to patrol officers right now. Axon Draft One uses your body-worn camera audio to generate a draft narrative within several minutes of incident completion: the Leon County Sheriff's Office documented average report time dropping. If you run several reports per shift, that's many minutes per shift recovered for patrol. The critical discipline: read and edit every draft before submission. You sign it, if the AI draft has a factual error or a legal element missing, that is on you, not on the software. States including Utah and California now require AI-disclosure statements on AI-assisted reports; follow your agency's policy exactly.
AI is sitting alongside you hereOperate body-worn camera (BWC) systems, activating the BWC at the start of enforcement contacts per departmental policy, ensuring footage is properly tagged with the incident number before upload, reviewing recorded footage to refresh memory before writing reports, and producing footage in response to supervisory requests, public records requests, or court subpoenas.
Operate body-worn camera (BWC) systems, activating the BWC at the start of enforcement contacts per departmental policy, ensuring footage is properly tagged with the incident number before upload, reviewing recorded footage to refresh memory before writing reports, and producing footage in response to supervisory requests, public records requests, or court subpoenas.[12],[13]
Your body-worn camera is both your protection and your accountability. The footage that exonerates you on a false complaint is the same footage a supervisor will review to evaluate your professionalism on every interaction: Truleo analyzes 100% of BWC audio for officer communication patterns, including the level of explanation given to subjects during stops. Officers who naturally explain what they are doing ('I am stopping you because the plate on this vehicle came back stolen') perform better on professionalism metrics and have better community interaction outcomes. Think of the camera as your most reliable witness and write reports that are consistent with what it captured.
AI is sitting alongside you hereMonitor and coordinate drone-as-first-responder (DFR) program operations, requesting drone deployment through the dispatch or RTCC interface when available, reviewing live drone feed on a mobile device or in-car screen before arriving on scene, using aerial surveillance to locate fleeing suspects or missing persons, and documenting drone observations in the incident report.
Monitor and coordinate drone-as-first-responder (DFR) program operations, requesting drone deployment through the dispatch or RTCC interface when available, reviewing live drone feed on a mobile device or in-car screen before arriving on scene, using aerial surveillance to locate fleeing suspects or missing persons, and documenting drone observations in the incident report.[10],[14]
Drone programs are reshaping the earliest minutes of a call response: IACP 2025 data shows DFR-equipped departments arriving on scene in minutes and clearing 20-40% of calls without officer dispatch at all. In departments where you will be the on-scene officer after drone observation, learn to read aerial footage quickly: a drone's top-down perspective reveals subject positions, vehicle locations, and exit routes that are invisible from street level. Departments are also deploying drones for active pursuits and missing-person searches, volunteering to train as a drone operator broadens your assignment options and adds a demonstrable technical skill to your personnel file.
Where police officers go next
Natural next steps for someone with your foundation: not exits, evolutions.
- First-Line Supervisors of Police and Detectives
- US median pay
- $106,040 (May 2025)
- BLS outlook 2025-35
- +3.3%
- Detectives and Criminal Investigators
- US median pay
- $93,790 (May 2025)
- BLS outlook 2025-35
- +0.2%
- Parking Enforcement WorkersNo timeline for this role yet
- Security Guards
- US median pay
- $38,020 (May 2025)
- BLS outlook 2025-35
- +0.9%
What each move takes
First-Line Supervisors of Police and Detectives
Promotion to sergeant (first-line supervisor) is the standard first promotion in most U.S. law enforcement agencies, typically requiring several years of patrol experience, a written civil service examination, an oral board, and in some departments an assessment center. Sergeants supervise several patrol officers per shift, review reports, authorize use-of-force reports, handle citizen complaints, and manage personnel documentation. The role leans heavier on administrative work than patrol, but the Axon Draft One and Fusus RTCC tools that help patrol officers also accelerate sergeant-level administrative work. A sizeable share of current commissioned personnel will be retirement-eligible by January 2025 per PERF: the sergeant rank will see above-average turnover and above-average promotion opportunity.
How has the work of police officers changed since 1845?
The tools that defined the work, one line per era. Select an era to see how it reshaped the work.
Walking beat + nightstick + whistle (foot-patrol era)
The foundational tool kit of the first American patrol officer was almost entirely physical: a wooden nightstick or baton (the primary use-of-force instrument), a police whistle to summon help or signal alarm over distances of several city blocks, a lantern for night patrol, and the officer's own legs, four to eight miles of walking per shift, every shift. The knowledge required was local and relational: knowing the faces on the block, recognizing who belonged and who did not, maintaining what the era called "the peace" through presence rather than response. The patrolman in this era had no way to call for backup faster than running to the next beat officer or to the precinct house.
Effect on the workThe walking beat defined the patrol function as essentially indivisible from the officer's physical presence. No technology yet existed to extend or leverage that presence: every officer covered a fixed geography at foot speed, and staffing levels were the sole variable determining coverage.
Police call box + telegraph dispatch (first communication network)
The police call box (a cast-iron cabinet mounted on a street lamp post, connected by telegraph wire to the precinct house) was introduced in Albany, New York, in 1877 and rapidly adopted across US cities. The call box let a beat patrolman report a crime, request an ambulance, or summon the patrol wagon without abandoning his post. It also let the precinct sergeant track whether officers were walking their beats: the boxes often required officers to check in at scheduled intervals. The call box network was the first technology that integrated the isolated beat officer into a real-time command structure. For three decades it was the only way a patrolman on the street could communicate with headquarters faster than the time it took to run there.
Effect on the workCall boxes improved deployment responsiveness without reducing the need for officers; they extended the effective span of supervision and enabled the patrol wagon to replace foot-dragging prisoners to lockup.
Motorized patrol car + two-way police radio (command and mobility revolution)
By 1933, Bayonne, New Jersey had installed the first two-way police radio in a patrol car: the system where officers could both receive instructions from dispatch and respond. Within fifteen years, motorized patrol with two-way radio had largely displaced the walking beat as the dominant patrol model in American cities. A single officer in a patrol car could cover a geographic area in minutes that a foot patrol officer could cover in hours. Police response times fell. The patrol car became the central icon of American policing, and the source of a lasting tension between rapid response and community knowledge.
Effect on the workThe patrol car dramatically increased the geographic coverage per officer, enabling some cities to reduce patrol staffing ratios. It also centralized dispatch and removed local beat knowledge as the primary patrol asset, shifting expertise toward procedural compliance and rapid response.
911 emergency telephone system + CAD computer-aided dispatch (response infrastructure)
The first 911 call in the US was placed in Haleyville, Alabama, on February 16, 1968. By 1987, a large share of the US population was served by 911; by 1999, the figure exceeded 93%. The 911 system transformed police work in two ways: it standardized citizen access to emergency response, and it created an enormous new demand for patrol service. Prior to universal 911, most crime reporting required a citizen to visit a station house or find a patrol officer on the beat. After 911, every household could summon police by phone, and they did: call volumes exploded. Computer-Aided Dispatch (CAD) systems, introduced in the early 1970s and broadly deployed through the 1980s, managed this volume by routing calls to patrol units and tracking response times, creating the first systematic operational data on police performance.
Effect on the workUniversal 911 access substantially increased call-for-service volume, which drove patrol staffing growth through the 1970s and 1980s as departments tried to maintain response-time targets against rising call load.
CompStat + AFIS fingerprint databases + DNA analysis (data-driven policing)
CompStat, COMPuter STATistics, was launched by NYPD Commissioner William Bratton and Deputy Commissioner Jack Maple in January 1994. The system compiled daily crime statistics by precinct into a digital map and convened weekly command accountability meetings where precinct commanders were required to explain crime trends and demonstrate proactive responses. The CompStat model spread to virtually every large US police department within a decade. Simultaneously, the Automated Fingerprint Identification System (AFIS), developed by the FBI through the 1970s–80s and broadly networked nationally through the 1990s, transformed detective work by enabling rapid comparison of latent prints against national databases. DNA analysis, first used in a US criminal conviction in 1988, became a standard investigative tool through the 1990s.
Effect on the workCompStat created substantial managerial pressure on patrol officers: precinct commanders facing weekly statistical accountability pushed officers toward higher-activity policing (stop-and-frisk, broken windows enforcement) that generated documented numbers. The data-driven era produced measurable crime reduction and also the conditions that led to the 2020 reckoning.
Body-worn cameras + Tasers + LPR license-plate readers (accountability and sensing layer)
The police shooting of Michael Brown on August 9, 2014 in Ferguson, Missouri, and the subsequent DOJ federal investigations and consent decrees triggered an accelerated deployment of body-worn cameras across US police agencies. Axon (renamed from TASER International in 2017) captured the majority of the market; by 2016, a large share of local general-purpose police agencies had at least some body-worn cameras deployed. Simultaneously, Flock Safety (founded 2017) deployed automated license-plate reader cameras that automatically read and log every passing vehicle plate, flagging stolen cars and wanted persons in real time. By 2025 Flock reported operating in over 5,000 communities across many states.
Effect on the workBody-worn cameras added administrative time (reviewing footage, uploading to Evidence.com) without reducing patrol requirements; they substantially changed the culture of encounters by making officer conduct reviewable. LPR systems enabled a single officer to passively scan hundreds of plates per shift that previously required manual checks.
Drone-as-first-responder + Clearview AI facial recognition (autonomous sensing)
In May 2018, Chula Vista, California became the only municipal agency selected for the FAA's UAS Integration Pilot Program, launching the first operational Drone as First Responder (DFR) program in US law enforcement. A drone launched from one of four city-wide stations could reach a scene averaging two minutes before ground units, arriving first on crime in progress, serious accidents, and officer-needs-assistance calls. The program assisted in more than a hundred arrests and cleared hundreds of calls for service without dispatching ground officers in its first years. By 2024, many US cities had operational DFR programs. Clearview AI, founded in 2017 as SmartCheckr and revealed by a January 2020 New York Times investigation, provided facial recognition that could match a face against a database of more than 3 billion scraped social-media images. By 2023, US police had used Clearview AI's tools to conduct nearly one million searches across approximately 2,000 public agencies. The technology sparked legislative restriction in several states and cities.
Effect on the workDrone-as-first-responder programs enabled early scene intelligence without committing a sworn officer; in some cases calls were resolved by the drone without dispatching ground units, representing a genuine reduction in officer hours for certain call types. Facial recognition dramatically accelerated identity-matching but introduced documented error rates, particularly against darker-skinned individuals, that generated wrongful-arrest cases and restrictions.
Axon Draft One AI report-writer + predictive analytics (LLM augmentation era)
On April 23, 2024, Axon announced Draft One: a first-of-its-kind AI-powered police report writing tool that uses GPT-4 Turbo to transcribe body-worn camera audio and automatically draft a narrative police report in seconds. The tool reduces report-writing time in independent assessments; some agencies report up to 82% reduction in report time. In its first months, Draft One contributed to over 100,000 incident reports, saving a documented 2.2 million officer-minutes. Every draft requires review and approval by the submitting officer before submission: the AI writes, the officer owns. For a profession in which report writing has historically consumed a sizeable share of an officer's shift, Draft One represents the first LLM-era tool aimed at the actual daily workflow of a patrol officer. Axon built it atop Microsoft Azure OpenAI and calibrated it specifically to prevent speculation or embellishment: a critical constraint given that police reports are evidentiary documents.
Effect on the workIf Draft One and similar tools reduce report-writing burden per shift, the implications for authorized staffing levels are significant: departments operating below authorized strength may be able to achieve the same patrol coverage with fewer officers, or redeploy officer time from paperwork to patrol. This is the AI-augmentation scenario for policing: the officer stays, the administrative burden shrinks.
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Browse all rolesPolice and Sheriff's Patrol Officers employment and pay by year
In other countries
The latest figure each country's statistics agency publishes for this job. Each uses its own occupation definition, survey basis and currency, so the numbers are not directly comparable with each other or with the US figures.
Canada (NOC 42100)
- Employment, 2020
- 73,090, Statistics Canada Census 2021 Official statistic Report an errorStatistics Canada Census of Population 2021: number of persons with employment income in NOC 42100 Police officers (except commissioned), Canada, reference year 2020. A recipients basis (anyone with employment income during the year), slightly broader than a point-in-time employed count. Statistics Canada Open Licence.
- Median pay, 2020
- C$111,000, Statistics Canada Census 2021 Official statistic Report an errorStatistics Canada Census of Population 2021 (Table 98-10-0586): median employment income for NOC 42100 Police officers (except commissioned), Canada, reference year 2020, full-year full-time workers (the basis comparable to the US OEWS full-time median). Statistics Canada Open Licence.
United Kingdom (UK SOC 3312)
- Employment, 2022
- 289,000, ONS ASHE 2022 Official statistic Report an errorONS Annual Survey of Hours and Earnings (Table 14): employee jobs in SOC 3312 Police officers (sergeant and below), United Kingdom, 2022 (ASHE "number of jobs", thousands x1000; excludes self-employment). Open Government Licence v3.0.
- Median pay, 2022
- £44,037, ONS ASHE 2022 Official statistic Report an errorONS Annual Survey of Hours and Earnings (Table 14.7a): median gross annual pay for all employee jobs in SOC 3312 Police officers (sergeant and below), United Kingdom, 2022. Open Government Licence v3.0.
Australia (ANZSCO 4413)
- Employment, 2025
- 75,300, ABS Labour Force Survey March 2026 Official statistic Report an errorABS Labour Force Survey (Detailed), table EQ08: employed persons in ANZSCO 4413 Police, national (summed across sex and state/territory), annual average of 4 quarterly estimates.
- Median pay, 2025
- A$133,120, ABS Employee Earnings May 2025 Official statistic Report an errorAnnualised (x52) from A$2,560 median weekly earnings. ABS Survey of Employee Earnings and Hours, May 2025: median pay for full-time non-managerial employees paid at the adult rate, before tax. Surfaced via the Jobs and Skills Australia occupation profile for ANZSCO 4413.
View all 28 years of cited US data, each linked to its source
| Year | US employment | Annual pay (median unless marked) | Source | Report |
|---|---|---|---|---|
| 1900 | 60,000 | n/a | Est., BJS Researched context | Report |
| 1930 | 130,000 | n/a | Est., FBI Uniform Crime Reporting Program Researched context | Report |
| 1960 | 200,000 | n/a | Est., FBI Researched context | Report |
| 1975 | 315,000 | $13,500 | Est., Presley Center UCR Data Compendium (employment) Researched contextEst., Bureau of Labor Statistics (pay) Researched context | Report |
| 2000 | 571,210 | $39,000 | BLS OEWS 2000 (employment) Official statisticEst., BLS Occupational Outlook Handbook (pay) Researched context | Report |
| 2003 | 609,960 | $44,020 | BLS OEWS May 2003 Official statistic | Report |
| 2004 | 616,340 | $45,210 | BLS OEWS May 2004 Official statistic | Report |
| 2005 | 624,130 | $46,290 | BLS OEWS May 2005 Official statistic | Report |
| 2006 | 624,380 | $47,460 | BLS OEWS May 2006 Official statistic | Report |
| 2007 | 625,880 | $49,630 | BLS OEWS May 2007 Official statistic | Report |
| 2008 | 633,710 | $51,410 | BLS OEWS May 2008 Official statistic | Report |
| 2009 | 641,590 | $53,210 | BLS OEWS May 2009 Official statistic | Report |
| 2010 | 644,300 | $53,540 | BLS OEWS May 2010 Official statistic | Report |
| 2011 | 636,410 | $54,230 | BLS OEWS May 2011 Official statistic | Report |
| 2012 | 632,000 | $55,270 | BLS OEWS May 2012 Official statistic | Report |
| 2013 | 635,380 | $56,130 | BLS OEWS May 2013 Official statistic | Report |
| 2014 | 638,810 | $56,810 | BLS OEWS May 2014 Official statistic | Report |
| 2015 | 653,740 | $58,320 | BLS OEWS May 2015 Official statistic | Report |
| 2016 | 657,690 | $59,680 | BLS OEWS May 2016 Official statistic | Report |
| 2017 | 662,390 | $61,050 | BLS OEWS May 2017 Official statistic | Report |
| 2018 | 661,330 | $61,380 | BLS OEWS May 2018 Official statistic | Report |
| 2019 | 665,280 | $63,150 | BLS OEWS May 2019 (employment) Official statisticBLS OEWS May 2019 (pay) Official statistic | Report |
| 2020 | 654,900 | $65,540 | BLS OEWS May 2020 Official statistic | Report |
| 2021 | 665,380 | $64,610 | BLS OEWS May 2021 Official statistic | Report |
| 2022 | 655,890 | $65,790 | BLS OEWS May 2022 Official statistic | Report |
| 2023 | 646,310 | $72,280 | BLS OEWS May 2023 (employment) Official statisticBLS OEWS May 2023 (pay) Official statistic | Report |
| 2024 | 666,990 | $76,290 | BLS OEWS May 2024 Official statistic | Report |
| 2025 | 670,520 | $76,210 | BLS OEWS May 2025 Official statistic | Report |
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