Police Officers
Overall Exposure
2025 vs 2023
Theoretical Exposure
20What AI could do
Observed Exposure
5What AI actually does
Automation Risk Score
7Displacement risk
3-Year Outlook (2025 → 2028)
Projected changes in AI automation metrics over the next 3 years based on estimated data.
Overall Exposure
2025 → 2028 (estimated)
Theoretical Exposure
2025 → 2028 (estimated)
Observed Exposure
2025 → 2028 (estimated)
Automation Risk
2025 → 2028 (estimated)
Exposure Metrics (2023 - 2028)
Task Breakdown
About This Occupation
If you work as a Police Officers, AI is reshaping your profession. With an automation risk of 7/100 and overall exposure at 12%, this role faces low transformation. The highest-impact area is patrol areas at 3% automation. This is classified as an 'augment' role. BLS projects +3% growth through 2034. Professionals who embrace AI tools will see their capabilities significantly amplified.
ISCO-08 classification
Police Officers
Indirect mapping — this occupation is linked to the ISCO unit group by a rule-based fallback.
Definition
ILO original text (English)
Police officers maintain law and order, patrolling public areas, enforcing laws and regulations and arresting suspected offenders.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET33-3051.00
Police and Sheriff's Patrol Officers
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.
View original - ONET33-3052.00
Transit and Railroad Police
Protect and police railroad and transit property, employees, or passengers.
View original
Frequently Asked Questions
With an automation risk score of 7%, Police Officers has a low risk of AI replacement. Most tasks in this role require skills that are difficult for AI to replicate, such as complex decision-making, physical dexterity, or deep interpersonal interaction. AI is more likely to serve as a supportive tool.
Our estimated AI automation risk score for Police Officers is 7% for 2025. Estimated overall AI exposure is 12%, with 20% theoretical exposure and 5% observed exposure. The estimated risk trend from 2023 to 2025 is +2 points. All of these are model-generated estimates, not measurements.
The tasks with the highest automation potential for Police Officers are: Patrol areas (3%). These rates are our own estimates of how much of each task current AI systems can handle. They are not measurements and are not taken from any external dataset.
We estimate a +3% employment change for Police Officers between 2024 and 2034. This is our own estimate, not a figure published by the U.S. Bureau of Labor Statistics. Combined with an estimated overall AI exposure of 12%, this occupation faces both traditional labor market shifts and AI-driven transformation. Workers should monitor both employment trends and AI capability growth.
Since AI primarily augments capabilities in this role, professionals in Police Officers should embrace AI as a productivity multiplier. Focus on learning to use AI tools effectively, developing higher-order analytical and creative skills, and positioning yourself as someone who can leverage AI to deliver greater value.