# Private Detectives and Investigators

> Gather, analyze, compile, and report information regarding individuals or organizations to clients, or detect occurrences of unlawful acts or infractions of rules in private establishment.

- **SOC code:** 33-9021.00
- **Canonical URL:** https://singulariki.com/roles/role-33-9021-00
- **Also known as:** Investigator, Loss Prevention Detective, Loss Prevention Officer, Private Investigator, Asset Protection Detective, Field Investigator, Loss Prevention Agent, Loss Prevention Associate
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Write reports or case summaries to document investigations.
- Conduct private investigations on a paid basis.
- Search computer databases, credit reports, public records, tax or legal filings, or other resources to locate persons or to compile information for investigations.
- Expose fraudulent insurance claims or stolen funds.
- Conduct personal background investigations, such as pre-employment checks, to obtain information about an individual's character, financial status, or personal history.
- Obtain and analyze information on suspects, crimes, or disturbances to solve cases, to identify criminal activity, or to gather information for court cases.
- Testify at hearings or court trials to present evidence.
- Question persons to obtain evidence for cases of divorce, child custody, or missing persons or information about individuals' character or financial status.
- Observe and document activities of individuals to detect unlawful acts or to obtain evidence for cases, using binoculars and still or video cameras.
- Investigate companies' financial standings, or locate funds stolen by embezzlers, using accounting skills.
- Perform undercover operations, such as evaluating the performance or honesty of employees by posing as customers or employees.
- Alert appropriate personnel to suspects' locations.

**Emerging tasks** (O*NET):
- Serve documents to parties named in legal proceedings.
- Use advanced technology, such as drones, GPS trackers, and surveillance cameras, to facilitate investigations.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- English Language _(knowledge)_
- Customer and Personal Service _(knowledge)_
- Active Listening _(essential_skill)_
- Inductive Reasoning _(ability)_
- Law and Government _(knowledge)_
- Speaking _(essential_skill)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Problem Sensitivity _(ability)_
- Near Vision _(ability)_
- Reading Comprehension _(essential_skill)_
- Critical Thinking _(essential_skill)_

**Skills in demand:**
- English Language _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Writing _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Social Perceptiveness _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Excel _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Word _(hot technology, in demand)_
- Facebook _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Windows _(hot technology)_
- Computer imaging software
- Email software
- LexisNexis
- Web browser software

## AI exposure & outlook

- **AI task-overlap index:** 59th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 66th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 56th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 59th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 39th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 6.0% growth (About average); 3.9k annual openings; 43.6k → 46.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $52,370; 38,700 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** — automation, 39% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** learning.

**Tasks most handed to AI here:**
- Obtain and analyze information on suspects, crimes, or disturbances to solve cases, to identify criminal activity, or to gather information for court cases. _(0.4% of measured AI use; learning)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me obtain and analyze information on suspects, crimes, or disturbances to solve cases, to identify criminal activity, or to gather information for court cases.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-33-9021-00_