Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Prepare written opinions and decisions. · 2.9%
Administrative Law Judges, Adjudicators, and Hearing Officers
Occupation · SOC 23-1021.00
Conduct hearings to recommend or make decisions on claims concerning government programs or other government-related matters. Determine liability, sanctions, or penalties, or recommend the acceptance or rejection of claims or settlements.
Also called: Administrative Hearings Officer · Administrative Judge · Administrative Law Judge · Hearings Officer · Adjudications Specialist · Adjudicator · Appeals Examiner · Appeals Referee · Claims Adjudicator · Workers' Compensation Hearings Officer · Administrative Hearing Officer · Appeals Officer
Job family: Legal Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-23-1021-00/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.
Use as a copilot
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
- Determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence. · 9.2%
- Research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions. · 1.4%
Keep a human in the loop
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
- Prepare written opinions and decisions. · 96.9% need a human
- Determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence. · 87.9% need a human
- Research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions. · 82.4% need a human
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 →Market signal
Independent published positions, read together — not a forecast.
- Declining employment outlook (-0.7% by 2034)
- 500 openings/yr
- Moderate AI exposure
- Observed AI use leans augmentation
- Median pay $115,230/yr
- Can largely be done remotely (teleworkable)
- Both the 2013 computerization estimate and today's AI exposure rank this high
70th-percentile task overlap — yet about 500 openings a year (-0.7% projected, BLS), and observed AI use leans 5546% copilot, not hand-off (AEI) . 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.) High | 94th | 1.4 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 71st | 0.8 | |
| AI assistant applicability (Microsoft) Moderate | 46th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.5), and including AI-powered software (γ 0.8). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
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 0.6 · 54th 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.
| Determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence. | 14.9% | |
| Research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions. | 3.0% | |
| Prepare written opinions and decisions. | 1.6% | |
| Explain to claimants how they can appeal rulings that go against them. | 0.2% |
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 | 500 |
| Employment 2024 → 2034 | 17,500 → 17,400 |
“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.
Administrative Law Judges, Adjudicators, and Hearing Officers sits at the 59th 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.
31% mean task exposure (2025)
59th percentile of 427 placed occupations
+4 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Judges · 2612 | 31% | 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.
Working with AI in this job
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 55.5% working with AI · 41.9% handed to AI |
| Most common way people use AI here | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 3.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 72.7% |
What people delegate to AI
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence. | Iteration | 9.2% |
| Prepare written opinions and decisions. | Directive | 2.9% |
| Research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions. | Learning | 1.4% |
Where a human is still needed
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Prepare written opinions and decisions. | 96.9% | |
| Determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence. | 87.9% | |
| Research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions. | 82.4% |
What people most often hand AI here
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
-
Help me determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence.From: Determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence. · 9.2% of measured AI use · task iteration
-
Help me prepare written opinions and decisions.From: Prepare written opinions and decisions. · 2.9% of measured AI use · directive
-
Help me research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions.From: Research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions. · 1.4% of measured AI use · learning
Tasks
All 14 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence. Core · importance 4.7
- Monitor and direct the activities of trials and hearings to ensure that they are conducted fairly and that courts administer justice while safeguarding the legal rights of all involved parties. Core · importance 4.7
- Prepare written opinions and decisions. Core · importance 4.7
- Authorize payment of valid claims and determine method of payment. Core · importance 4.6
- Conduct hearings to review and decide claims regarding issues, such as social program eligibility, environmental protection, or enforcement of health and safety regulations. Core · importance 4.6
- Research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions. Core · importance 4.5
- Review and evaluate data on documents, such as claim applications, birth or death certificates, or physician or employer records. Core · importance 4.4
- Recommend the acceptance or rejection of claims or compromise settlements according to laws, regulations, policies, and precedent decisions. Core · importance 4.3
- Rule on exceptions, motions, and admissibility of evidence. Core · importance 4.3
- Explain to claimants how they can appeal rulings that go against them. Core · importance 4.2
- Schedule hearings. Supplemental · importance 4.1
- Confer with individuals or organizations involved in cases to obtain relevant information. Core · importance 4.0
- Issue subpoenas and administer oaths in preparation for formal hearings. Core · importance 3.8
- Conduct studies of appeals procedures in field agencies to ensure adherence to legal requirements and to facilitate determination of cases. Supplemental · importance 3.6
Work activities
- Coordinate legal schedules or activities.
- Prepare written decisions for legal proceedings.
- Evaluate information related to legal matters in public or personal records.
- Research relevant legal materials to aid decision making.
- Identify implications for cases from legal precedents or other legal information.
- Interview claimants to get information related to legal proceedings.
- Provide legal advice to clients.
- Direct courtroom activities or procedures.
- Authorize payments to settle legal disputes.
- Make decisions in legal cases.
- Conduct hearings to investigate legal issues.
- Rule on admissibility of legal proceedings.
- Prepare legal documents.
- Administer oaths to court participants.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Law and Government | 4.8 | |
| English Language | 4.1 | |
| Customer and Personal Service | 3.9 | |
| Administrative | 3.4 | |
| Medicine and Dentistry | 3.3 | |
| Administration and Management | 3.3 |
Essential skills
| Reading Comprehension | 4.3 | |
| Active Listening | 4.3 | |
| Critical Thinking | 4.3 | |
| Writing | 4.1 | |
| Speaking | 4.0 | |
| Active Learning | 3.8 | |
| Monitoring | 3.6 | |
| Learning Strategies | 3.0 |
Abilities
| Oral Comprehension | 4.3 | |
| Written Comprehension | 4.3 | |
| Inductive Reasoning | 4.3 | |
| Written Expression | 4.1 | |
| Deductive Reasoning | 4.1 | |
| Oral Expression | 4.0 | |
| Problem Sensitivity | 4.0 | |
| Speech Clarity | 3.9 | |
| Information Ordering | 3.8 | |
| Near Vision | 3.8 | |
| Speech Recognition | 3.8 | |
| Category Flexibility | 3.1 | |
| Selective Attention | 3.1 | |
| Fluency of Ideas | 2.9 | |
| Originality | 2.9 | |
| Flexibility of Closure | 2.9 |
Transferable skills
| Judgment and Decision Making | 4.1 | |
| Social Perceptiveness | 3.9 | |
| Complex Problem Solving | 3.9 | |
| Negotiation | 3.3 | |
| Time Management | 3.3 | |
| Coordination | 3.0 | |
| Persuasion | 3.0 | |
| Service Orientation | 3.0 | |
| Instructing | 2.8 | |
| Systems Analysis | 2.8 |
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 42.
Tools & technology
| Example | Category | |
|---|---|---|
| Microsoft Office software | Office suite software | Hot technology In demand |
| Adobe Acrobat | Document management software | Hot technology |
| Microsoft Access | Data base user interface and query software | Hot technology |
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Outlook | Electronic mail software | Hot technology |
| Microsoft PowerPoint | Presentation software | Hot technology |
| Microsoft Windows | Operating system software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
| SAP software | Enterprise resource planning ERP software | Hot technology |
| Courtroom scheduling software | Legal management software | |
| Email software | Electronic mail software | |
| LexisNexis | Information retrieval or search software | |
| Online databases | Data base user interface and query software | |
| Thomson Reuters Westlaw | Information retrieval or search software | |
| Videoconferencing software | Video conferencing software | |
| Web browser software | Internet browser software |
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 5 — Job Zone Five: Extensive Preparation Needed
- Education
- Most of these occupations require graduate school. For example, they may require a master's degree, and some require a Ph.D., M.D., or J.D. (law degree).
- Typical entry-level education
- Doctoral or professional degree · BLS, the typical path — not a requirement
- Related experience
- Extensive skill, knowledge, and experience are needed for these occupations. Many require more than five years of experience. For example, surgeons must complete four years of college and an additional five to seven years of specialized medical training to be able to do their job.
- Preparation level
- SVP (8.0 and above) — total schooling plus on-the-job experience.
What to study: Legal Professions and Studies . 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.
| Doctoral Degree | 37.3% | |
| Bachelor's Degree | 19.9% | |
| First Professional Degree | 13.8% | |
| Some College Courses | 11.2% | |
| Associate's Degree (or other 2-year degree) | 11.2% | |
| Post-Doctoral Training | 5.1% | |
| Master's Degree | 1.4% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Work styles
| Dependability | 8.0 | |
| Attention to Detail | 7.0 | |
| Integrity | 6.0 | |
| Cautiousness | 5.0 | |
| Intellectual Curiosity | 4.0 | |
| Self-Control | 3.0 |
Interest areas
| Law | 6.8 | |
| Management/Administration | 4.4 | |
| Public Speaking | 4.1 | |
| Office Work | 3.1 | |
| Politics | 2.5 | |
| Social Science | 2.5 |
Career interests (Holland / RIASEC)
| Conventional | 5.5 | |
| Enterprising | 5.1 | |
| Investigative | 4.0 | |
| Social | 3.0 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $56,970 |
| 25th percentile | $76,920 |
| Median (50th) | $115,230 |
| 75th percentile | $161,290 |
| 90th percentile | $203,990 |
| People employed | 16,230 |
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 |
|---|---|---|
| Educational Services · Sector | 30 | $103,870 |
Related occupations
Part of the Public Service & Safety career cluster.
- Judges, Magistrate Judges, and Magistrates · 23-1023.00 Compare →
- Judicial Law Clerks · 23-1012.00 Compare →
- Lawyers · 23-1011.00 Compare →
- Arbitrators, Mediators, and Conciliators · 23-1022.00 Compare →
- Claims Adjusters, Examiners, and Investigators · 13-1031.00 Compare →
- Equal Opportunity Representatives and Officers · 13-1041.03 Compare →
- Probation Officers and Correctional Treatment Specialists · 21-1092.00 Compare →
- Labor Relations Specialists · 13-1075.00 Compare →
- Fraud Examiners, Investigators and Analysts · 13-2099.04 Compare →
- Chief Executives · 11-1011.00 Compare →
- Paralegals and Legal Assistants · 23-2011.00 Compare →
- Court, Municipal, and License Clerks · 43-4031.00 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 Administrative Law Judges, Adjudicators, and Hearing 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.
- Doctoral or professional degree · typical entry level
- Job zone 5 — Job Zone Five: Extensive Preparation Needed · preparation tier
- Legal Professions and Studies · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 59th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Administrative Law Judges, Adjudicators, and Hearing Officers show 70th-percentile AI task overlap — and about 500 annual U.S. openings
- Administrative Law Judges, Adjudicators, and Hearing Officers rank in the 70th percentile (High 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 500 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 $115,230, across about 16,230 U.S. workers.BLS OEWS (May 2024)
- Of the AI use actually observed for this work, 55% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Administrative Law Judges, Adjudicators, and Hearing Officers show 70th-percentile AI task overlap — and about 500 annual U.S. openings • Administrative Law Judges, Adjudicators, and Hearing Officers rank in the 70th percentile (High 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 500 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 $115,230, across about 16,230 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 55% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Administrative Law Judges, Adjudicators, and Hearing Officers". https://singulariki.com/roles/role-23-1021-00 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. "Administrative Law Judges, Adjudicators, and Hearing 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-23-1021-00
APA
Singulariki. (2026). Administrative Law Judges, Adjudicators, and Hearing Officers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-23-1021-00
BibTeX
@misc{singulariki-role-23-1021-00,
title = {Administrative Law Judges, Adjudicators, and Hearing 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-23-1021-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.