Community Sentiment
Do you agree?
Do you agree with the AI automation risk score calculated for this occupation?
AI Automation Index
Will AI Replace Administrative Law Judges, Adjudicators, and Hearing Officers?
Task-level automation exposure for Administrative Law Judges, Adjudicators, and Hearing Officers: 14 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
36%
weighted task index
14 of 14 tasks scored
Median Salary
$117,860 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
16,370 people hold this job — size, not growth
Projected 2025–35
0.0%
employment change
500 openings a year · BLS line item
Pay by state
BLS OEWS publishes 42 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$56,830 – $181,060
Highest medians
District of Columbia $181,060
Indiana $145,290
Alabama $134,810
Maryland $133,460
Wisconsin $132,250
Lowest medians
Delaware $56,830
Arkansas $63,660
Idaho $65,050
Mississippi $66,310
Georgia $67,990
State figures come from the 23-1021 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 36%
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 58%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 17%
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 11/100
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) 19%
3 tasks
Medium exposure (≥ 35%) 36%
5 tasks
Low exposure (below 35%) 45%
6 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 08/2026 · Occupational Expert
Review new case law or changes in laws or regulations to stay current on legal precedent.
Constituent Tasks
#7623 · Core · 20% automatable
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.
interpersonal — Courtroom direction is live legal authority
Direct courtroom activities or procedures.
#7617 · Core · 40% automatable
Prepare written opinions and decisions.
decision support — Legal decisions carry accountability; AI only drafts
Prepare written decisions for legal proceedings.
#7625 · Core · 15% automatable
Conduct hearings to review and decide claims regarding issues, such as social program eligibility, environmental protection, or enforcement of health and safety regulations.
interpersonal — Hearings are live human proceedings
Conduct hearings to investigate legal issues.
#7626 · Core · 15% automatable
Rule on exceptions, motions, and admissibility of evidence.
decision support — Admissibility rulings are judicial human acts
Rule on admissibility of legal proceedings.
#7619 · Core · 63% automatable
Research and analyze laws, regulations, policies, and precedent decisions to prepare for hearings and to determine conclusions.
information retrieval — Legal research strong, decision human
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.
#7627 · Core · 15% automatable
Determine existence and amount of liability according to current laws, administrative and judicial precedents, and available evidence.
decision support — Legal decisions are accountable human judgment
Make decisions in legal cases.
#7628 · Core · 37% automatable
Issue subpoenas and administer oaths in preparation for formal hearings.
text generation — Draft legal documents; attorney owns final
Prepare legal documents. Administer oaths to court participants.
#7622 · Core · 40% automatable
Explain to claimants how they can appeal rulings that go against them.
decision support — Legal advice carries licensure and liability; human owns
Provide legal advice to clients.
#21181 · Core · 55% automatable
Schedule hearings.
decision support — Legal scheduling coordination is largely clerical with judgment
Coordinate legal schedules or activities.
#7618 · Core · 64% automatable
Review and evaluate data on documents, such as claim applications, birth or death certificates, or physician or employer records.
information retrieval — Legal research strong, decision human
Evaluate information related to legal matters in public or personal records. Research relevant legal materials to aid decision making.
#7624 · Supplemental · 18% automatable
Authorize payment of valid claims and determine method of payment.
decision support — Settlement authorization is high-stakes human judgment
Authorize payments to settle legal disputes. Make decisions in legal cases.
#7620 · Supplemental · 30% automatable
Confer with individuals or organizations involved in cases to obtain relevant information.
interpersonal — Claimant interviews require human assessment
Interview claimants to get information related to legal proceedings.
#7621 · Supplemental · 40% automatable
Recommend the acceptance or rejection of claims or compromise settlements according to laws, regulations, policies, and precedent decisions.
decision support — Legal advice carries licensure and liability; human owns
Provide legal advice to clients.
#7629 · Supplemental · 66% automatable
Conduct studies of appeals procedures in field agencies to ensure adherence to legal requirements and to facilitate determination of cases.
information retrieval — Legal research strong, decision human
Research relevant legal materials to aid decision making.
Embed this calculator on your site ↓
Bloggers & authors: Embed this interactive calculator directly in your articles or comparison guides. It loads dynamically via a responsive iframe (auto-resizing to prevent double scrollbars) and provides a direct, high-value tool for your audience.
<div class="giniloh-calculator-embed" data-calculator="administrative-law-judges-adjudicators-and-hearing-officers"></div>
<script src="https://giniloh.com/embed.js" async></script> 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 →Related Article
Best AI Proof Jobs in a Changing Market
Worried robots are coming for your paycheck? You’re not alone—but the real story is far more hopeful. This guide cuts through the scare headlines to reveal exactly where smart, sustainable career opportunities exist right now. We’ve curated a list of true ai proof jobs—roles in healthcare, skilled trades, and cybersecurity that not only survive automation but thrive because of human judgment and empathy. You’ll get specific, money-making data on projected growth (the BLS says wind turbine technicians, for instance, will grow 44% by 2032), real salary ranges from active job listings, and a simple self-assessment quiz to identify your own most resilient path. Plus, we name companies hiring today and the niche job boards they use. Stop worrying and start planning—your secure career is closer than you think.
Read Article ->