AI Automation Index

Will AI Replace Private Detectives and Investigators?

Task-level automation exposure for Private Detectives and Investigators: 14 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

43% weighted task index

14 of 14 tasks scored

Median Salary

$51,220 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

35,580 people hold this job — size, not growth

Projected 2025–35

+5.5% employment change

3,200 openings a year · BLS line item

Pay by state

BLS OEWS publishes 50 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$39,060 – $76,480

Highest medians

Oregon $76,480

Connecticut $75,010

District of Columbia $72,720

Vermont $67,910

New Hampshire $65,370

Lowest medians

Mississippi $39,060

Oklahoma $39,680

Iowa $41,110

New Mexico $41,600

Missouri $41,600

State figures come from the 33-9021 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 43%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 0%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 4%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 18%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 9/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

14 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 28%

4 tasks

Medium exposure (≥ 35%) 21%

3 tasks

Low exposure (below 35%) 51%

7 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Emerging & rewritten tasks

Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.

New 07/2015 · Incumbent

Serve documents to parties named in legal proceedings.
New 05/2025 · AI/SME

Use advanced technology, such as drones, GPS trackers, and surveillance cameras, to facilitate investigations.

Constituent Tasks

#13095 · Core · 72% automatable

Write reports or case summaries to document investigations.

text generation — Incident reports drafted from facts; human reviews

Prepare investigation or incident reports.

#13099 · Core · 30% automatable

Conduct private investigations on a paid basis.

information retrieval — Records research aided; field investigation human

Investigate personal characteristics or activities of individuals.

#13096 · Core · 70% automatable

Search computer databases, credit reports, public records, tax or legal filings, or other resources to locate persons or to compile information for investigations.

information retrieval — Database queries for investigation details

Examine records or other types of data to investigate criminal activities. Use databases to locate investigation details or other information.

#20758 · Core · 30% automatable

Conduct personal background investigations, such as pre-employment checks, to obtain information about an individual's character, financial status, or personal history.

information retrieval — Records research aided; field investigation human

Investigate personal characteristics or activities of individuals.

#13106 · Core · 35% automatable

Expose fraudulent insurance claims or stolen funds.

decision support — AI aids analysis, investigation is human-led

Investigate crimes committed within organizations.

#13097 · Core · 58% automatable

Obtain and analyze information on suspects, crimes, or disturbances to solve cases, to identify criminal activity, or to gather information for court cases.

data analysis — Record screening aided, investigative judgment human

Examine records or other types of data to investigate criminal activities.

#13100 · Core · 15% automatable

Testify at hearings or court trials to present evidence.

interpersonal — Testimony carries legal accountability and live presence

Testify at legal or legislative proceedings.

#13101 · Core · 30% automatable

Question persons to obtain evidence for cases of divorce, child custody, or missing persons or information about individuals' character or financial status.

interpersonal — Investigative interviews require human rapport

Interview people to obtain information about actions or status of individuals.

#13102 · Core · 20% automatable

Observe and document activities of individuals to detect unlawful acts or to obtain evidence for cases, using binoculars and still or video cameras.

situated mobility — Surveillance and observation require physical presence

Observe individuals' activities to gather information or compile evidence. Record crime or accident scene evidence with video or still cameras.

#13107 · Core · 30% automatable

Confer with establishment officials, security departments, police, or postal officials to identify problems, provide information, or receive instructions.

interpersonal — Live incident response with agencies is human-led

Collaborate with law enforcement or security agencies to respond to incidents.

#13105 · Supplemental · 35% automatable

Investigate companies' financial standings, or locate funds stolen by embezzlers, using accounting skills.

decision support — AI aids analysis, investigation is human-led

Investigate crimes committed within organizations.

#13104 · Supplemental · 30% automatable

Perform undercover operations, such as evaluating the performance or honesty of employees by posing as customers or employees.

information retrieval — Records research aided; field investigation human

Investigate personal characteristics or activities of individuals.

#13103 · Supplemental · 60% automatable

Alert appropriate personnel to suspects' locations.

text generation — Relaying situation details is structured communication

Communicate situation details to appropriate personnel.

#13109 · Supplemental · 80% automatable

Count cash and review transactions, sales checks, or register tapes to verify amounts or to identify shortages.

data analysis — Balancing receipts is arithmetic, human handles discrepancies

Balance receipts.

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Community Sentiment

Do you agree?

Do you agree with the AI automation risk score calculated for this occupation?

Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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