Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Police Identification and Records Officers
Occupation · SOC 33-3021.02
Collect evidence at crime scene, classify and identify fingerprints, and photograph evidence for use in criminal and civil cases.
Also called: Crime Scene Investigator (CSI) · Crime Scene Technician · Criminalist · Forensic Specialist · Crime Lab Analyst (Crime Laboratory Analyst) · Evidence Technician (Evidence Tech) · Field Identification Specialist · Identification Technician (Identification Tech) · Latent Fingerprint Examiner · Police Officer · Accident Examiner · Accident Investigator
Job family: Protective Service Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-33-3021-02/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
- Declining employment outlook (-0.7% by 2034)
- 7,800 openings/yr
- Moderate AI exposure
- Median pay $93,580/yr
- Work is mostly on-site (not teleworkable)
- A reversal from 2013 — rated low automation risk then (40th), high AI task-overlap now (51st)
51st-percentile task overlap — yet about 7,800 openings a year (-0.7% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Moderate | 54th | 0.2 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 50th | 0.6 | |
| AI assistant applicability (Microsoft) Moderate | 48th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.3), and including AI-powered software (γ 0.6). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.3 · 40th percentile among occupations · Moderate
How AI is actually used in this job
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Coordinate or conduct instructional classes or in-services, such as citizen police academy classes and crime scene training for other officers. | 0.3% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -0.7% by 2034 |
| Projected annual openings | 7,800 |
| Employment 2024 → 2034 | 117,900 → 117,100 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Police Identification and Records Officers sits at the 42nd percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
23% mean task exposure (2025)
42nd percentile of 427 placed occupations
+3 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Police Inspectors and Detectives · 3355 | 23% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Tasks
All 15 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Photograph crime or accident scenes for evidence records. Core · importance 4.6
- Maintain records of evidence and write and review reports. Core · importance 4.5
- Submit evidence to supervisors, crime labs, or court officials for legal proceedings. Core · importance 4.4
- Testify in court and present evidence. Core · importance 4.4
- Look for trace evidence, such as fingerprints, hairs, fibers, or shoe impressions, using alternative light sources when necessary. Core · importance 4.3
- Identify, compare, classify, and file fingerprints, using systems such as Automated Fingerprint Identification System (AFIS) or the Henry Classification System. Supplemental · importance 4.3
- Dust selected areas of crime scene and lift latent fingerprints, adhering to proper preservation procedures. Core · importance 4.3
- Analyze and process evidence at crime scenes, during autopsies, or in the laboratory, wearing protective equipment and using powders and chemicals. Core · importance 4.2
- Package, store and retrieve evidence. Core · importance 4.2
- Process film and prints from crime or accident scenes. Supplemental · importance 4.1
- Perform emergency work during off-hours. Supplemental · importance 3.9
- Interview victims, witnesses, suspects, and other law enforcement personnel. Supplemental · importance 3.8
- Serve as technical advisor and coordinate with other law enforcement workers or legal personnel to exchange information on crime scene collection activities. Core · importance 3.7
- Create sketches and diagrams, by hand or computer software, to depict crime scenes. Core · importance 3.6
- Coordinate or conduct instructional classes or in-services, such as citizen police academy classes and crime scene training for other officers. Core · importance 3.4
Emerging tasks
Newer responsibilities O*NET has flagged as growing for this occupation.
- Use drone technology for aerial photography and videography of crime scenes.
Work activities
- Document legal or regulatory information.
- Write operational reports.
- Process forensic or legal evidence in accordance with procedures.
- Use databases to locate investigation details or other information.
- Analyze crime scene evidence.
- Collaborate with law enforcement or security agencies to share information.
- Direct employee training programs.
- Interview people to gather information about criminal activities.
- Draw detailed or technical illustrations.
- Record crime or accident scene evidence with video or still cameras.
- Testify at legal or legislative proceedings.
- Examine crime scenes to obtain evidence.
- Respond to emergencies to provide assistance.
- Record information about suspects or criminals.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Law and Government | 4.2 | |
| Administrative | 3.8 | |
| English Language | 3.8 | |
| Public Safety and Security | 3.6 | |
| Computers and Electronics | 3.5 | |
| Customer and Personal Service | 3.2 | |
| Education and Training | 3.0 |
Essential skills
| Active Listening | 3.9 | |
| Speaking | 3.9 | |
| Reading Comprehension | 3.8 | |
| Critical Thinking | 3.8 | |
| Writing | 3.3 | |
| Active Learning | 3.0 | |
| Monitoring | 3.0 |
Abilities
| Oral Comprehension | 3.9 | |
| Written Comprehension | 3.9 | |
| Oral Expression | 3.9 | |
| Deductive Reasoning | 3.9 | |
| Inductive Reasoning | 3.9 | |
| Information Ordering | 3.9 | |
| Near Vision | 3.9 | |
| Written Expression | 3.8 | |
| Speech Recognition | 3.6 | |
| Speech Clarity | 3.6 | |
| Problem Sensitivity | 3.5 | |
| Flexibility of Closure | 3.5 | |
| Category Flexibility | 3.4 | |
| Fluency of Ideas | 3.0 | |
| Perceptual Speed | 3.0 | |
| Selective Attention | 3.0 | |
| Arm-Hand Steadiness | 3.0 | |
| Far Vision | 3.0 | |
| Visual Color Discrimination | 3.0 | |
| Originality | 2.9 |
Transferable skills
| Social Perceptiveness | 3.0 | |
| Coordination | 3.0 | |
| Complex Problem Solving | 3.0 | |
| Judgment and Decision Making | 3.0 | |
| Time Management | 3.0 | |
| Instructing | 2.9 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 41.
Tools & technology
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 3 — Job Zone Three: Medium Preparation Needed
- Education
- Most occupations in this zone require training in vocational schools, related on-the-job experience, or an associate's degree.
- Typical entry-level education
- High school diploma or equivalent · BLS, the typical path — not a requirement
- Related experience
- Previous work-related skill, knowledge, or experience is required for these occupations. For example, an electrician must have completed three or four years of apprenticeship or several years of vocational training, and often must have passed a licensing exam, in order to perform the job.
- Preparation level
- SVP (6.0 to < 7.0) — total schooling plus on-the-job experience.
What to study: Homeland Security, Law Enforcement, Firefighting and Related Protective Services , Military Technologies and Applied Sciences , Natural Resources and Conservation . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 34.6% | |
| Some College Courses | 28.5% | |
| Bachelor's Degree | 24.9% | |
| Associate's Degree (or other 2-year degree) | 10.8% | |
| Post-Secondary Certificate | 1.2% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Work styles
| Dependability | 7.0 | |
| Attention to Detail | 6.0 | |
| Integrity | 5.0 | |
| Cautiousness | 4.0 | |
| Self-Control | 3.0 | |
| Stress Tolerance | 2.5 | |
| Perseverance | 2.1 |
Career interests (Holland / RIASEC)
| Conventional | 5.6 | |
| Realistic | 4.8 | |
| Investigative | 3.7 | |
| Enterprising | 2.9 |
Interest areas
| Protective Service | 5.0 | |
| Law | 3.3 | |
| Public Speaking | 2.6 | |
| Information Technology | 2.4 | |
| Office Work | 2.4 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $54,160 |
| 25th percentile | $68,390 |
| Median (50th) | $93,580 |
| 75th percentile | $120,080 |
| 90th percentile | $159,410 |
| People employed | 110,790 |
Wages and employment are reported by BLS for the broader occupation group this specialty belongs to (SOC 33-3021), not for the specialty alone.
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Transportation and Warehousing · Sector | 440 | $115,070 |
| Educational Services · Sector | 280 | $82,990 |
| Health Care and Social Assistance · Sector | 60 | $85,650 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Transportation and Warehousing · Sector | 0.08× | 440 |
| Educational Services · Sector | 0.03× | 280 |
Related occupations
Part of the Public Service & Safety career cluster.
- Forensic Science Technicians · 19-4092.00 Compare →
- Detectives and Criminal Investigators · 33-3021.00 Compare →
- Private Detectives and Investigators · 33-9021.00 Compare →
- Coroners · 13-1041.06 Compare →
- Intelligence Analysts · 33-3021.06 Compare →
- Fraud Examiners, Investigators and Analysts · 13-2099.04 Compare →
- Digital Forensics Analysts · 15-1299.06 Compare →
- Police and Sheriff's Patrol Officers · 33-3051.00 Compare →
- Compliance Officers · 13-1041.00 Compare →
- First-Line Supervisors of Police and Detectives · 33-1012.00 Compare →
- File Clerks · 43-4071.00 Compare →
- Statistical Assistants · 43-9111.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Police Identification and Records Officers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- High school diploma or equivalent · typical entry level
- Job zone 3 — Job Zone Three: Medium Preparation Needed · preparation tier
- Homeland Security, Law Enforcement, Firefighting and Related Protective Services · field of study
- Military Technologies and Applied Sciences · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 42nd percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Police Identification and Records Officers show 51st-percentile AI task overlap — and about 7,800 annual U.S. openings
- Police Identification and Records Officers rank in the 51st percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 7,800 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be declining (-0.7%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $93,580, across about 110,790 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Police Identification and Records Officers show 51st-percentile AI task overlap — and about 7,800 annual U.S. openings • Police Identification and Records Officers rank in the 51st percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 7,800 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be declining (-0.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $93,580, across about 110,790 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Police Identification and Records Officers". https://singulariki.com/roles/role-33-3021-02 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Police Identification and Records Officers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-33-3021-02
APA
Singulariki. (2026). Police Identification and Records Officers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-33-3021-02
BibTeX
@misc{singulariki-role-33-3021-02,
title = {Police Identification and Records Officers},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-33-3021-02}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.