Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Compile, record, and code results or data from interview or survey, using computer or specified form. · 2.6%
Interviewers, Except Eligibility and Loan
Occupation · SOC 43-4111.00
Interview persons by telephone, mail, in person, or by other means for the purpose of completing forms, applications, or questionnaires. Ask specific questions, record answers, and assist persons with completing form. May sort, classify, and file forms.
Also called: Admissions Clerk · Admissions Representative · Interviewer · Registration Clerk · Admitting Representative · Data Collection Assistant · Market Research Interviewer · Research Interviewer · Survey Interviewer · Telephone Interviewer · Admissions Advisor · Admissions Associate
Job family: Office and Administrative Support Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-43-4111-00/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.
- Identify and report problems in obtaining valid data. · 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.
- Ask questions in accordance with instructions to obtain various specified information, such as person's name, address, age, religious preference, or state of residency. · 98.1% need a human
- Identify and report problems in obtaining valid data. · 97.1% need a human
- Compile, record, and code results or data from interview or survey, using computer or specified form. · 93.9% 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 (-11.6% by 2034)
- 15,800 openings/yr
- High AI exposure
- Observed AI use leans automation
- Median pay $43,830/yr
- Can largely be done remotely (teleworkable)
- Both the 2013 computerization estimate and today's AI exposure rank this high
78th-percentile task overlap — yet about 15,800 openings a year (-11.6% projected, BLS), and observed AI use leans 3200% 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 | 87th | 1.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 68th | 0.8 | |
| AI assistant applicability (Microsoft) High | 76th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.5), with simple added tooling (β 0.7), 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 0.9 · 86th percentile among occupations · High
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.
| Compile, record, and code results or data from interview or survey, using computer or specified form. | 9.3% | |
| Ask questions in accordance with instructions to obtain various specified information, such as person's name, address, age, religious preference, or state of residency. | 3.8% | |
| Identify and report problems in obtaining valid data. | 3.2% | |
| Prepare reports to provide answers in response to specific problems. | 1.9% | |
| Explain survey objectives and procedures to interviewees and interpret survey questions to help interviewees' comprehension. | 0.4% | |
| Assist individuals in filling out applications or questionnaires. | 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 · -11.6% by 2034 |
| Projected annual openings | 15,800 |
| Employment 2024 → 2034 | 164,300 → 145,100 |
“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.
Interviewers, Except Eligibility and Loan sits at the 92nd percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
55% mean task exposure (2025)
92nd percentile of 427 placed occupations
−16 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Survey and Market Research Interviewers · 4227 | 55% | Gradient 3 |
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 | 32.0% working with AI · 49.8% 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) | 58.7% |
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 |
|---|---|---|
| Compile, record, and code results or data from interview or survey, using computer or specified form. | Directive | 2.6% |
| Identify and report problems in obtaining valid data. | Validation | 1.4% |
| Ask questions in accordance with instructions to obtain various specified information, such as person's name, address, age, religious preference, or state of residency. | none | 0.5% |
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.
| Ask questions in accordance with instructions to obtain various specified information, such as person's name, address, age, religious preference, or state of residency. | 98.1% | |
| Identify and report problems in obtaining valid data. | 97.1% | |
| Compile, record, and code results or data from interview or survey, using computer or specified form. | 93.9% |
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 compile, record, and code results or data from interview or survey, using computer or specified form.From: Compile, record, and code results or data from interview or survey, using computer or specified form. · 2.6% of measured AI use · directive
-
Help me identify and report problems in obtaining valid data.From: Identify and report problems in obtaining valid data. · 1.4% of measured AI use · validation
-
Help me ask questions in accordance with instructions to obtain various specified information, such as person's name, address, age, religious preference, or state of residency.From: Ask questions in accordance with instructions to obtain various specified information, such as person's name, address, age, religious preference, or state of residency. · 0.5% of measured AI use · none
Tasks
All 17 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Ask questions in accordance with instructions to obtain various specified information, such as person's name, address, age, religious preference, or state of residency. Core · importance 4.6
- Locate and list addresses and households. Supplemental · importance 4.4
- Ensure payment for services by verifying benefits with the person's insurance provider or working out financing options. Core · importance 4.4
- Identify and report problems in obtaining valid data. Core · importance 4.4
- Perform office duties, such as telemarketing or customer service inquiries, maintaining staff records, billing patients, or receiving payments. Core · importance 4.3
- Review data obtained from interview for completeness and accuracy. Core · importance 4.3
- Compile, record, and code results or data from interview or survey, using computer or specified form. Core · importance 4.2
- Perform patient services, such as answering the telephone or assisting patients with financial or medical questions. Core · importance 4.1
- Assist individuals in filling out applications or questionnaires. Core · importance 4.1
- Identify and resolve inconsistencies in interviewees' responses by means of appropriate questioning or explanation. Core · importance 4.0
- Contact individuals to be interviewed at home, place of business, or field location, by telephone, mail, or in person. Supplemental · importance 3.9
- Supervise or train other staff members. Core · importance 3.9
- Collect and analyze data, such as studying old records, tallying the number of outpatients entering each day or week, or participating in federal, state, or local population surveys as a Census Enumerator. Supplemental · importance 3.6
- Prepare reports to provide answers in response to specific problems. Core · importance 3.6
- Explain survey objectives and procedures to interviewees and interpret survey questions to help interviewees' comprehension. Supplemental · importance 3.6
- Meet with supervisor daily to submit completed assignments and discuss progress. Core · importance 3.5
- Recruit participants for focus groups. Supplemental
Work activities
- Supervise clerical or administrative personnel.
- Collect deposits, payments or fees.
- Interview employees, customers, or others to collect information.
- Compile data or documentation.
- Code data or other information.
- Check data for recording errors.
- Assist individuals with paperwork.
- Verify accuracy of financial or transactional data.
- Negotiate financial arrangements.
- Resolve operational performance problems.
- Explain regulations, policies, or procedures.
- Answer telephones to direct calls or provide information.
- Prepare research or technical reports.
- Obtain personal or financial information about customers or applicants.
- Confer with coworkers to coordinate work activities.
- Analyze operational or research data.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
Essential skills
| Active Listening | 4.0 | |
| Speaking | 3.9 | |
| Reading Comprehension | 3.5 | |
| Writing | 3.3 | |
| Critical Thinking | 3.3 | |
| Monitoring | 3.0 | |
| Active Learning | 2.9 | |
| Learning Strategies | 2.9 |
Abilities
| Oral Expression | 4.0 | |
| Oral Comprehension | 3.9 | |
| Speech Recognition | 3.9 | |
| Speech Clarity | 3.9 | |
| Written Comprehension | 3.5 | |
| Written Expression | 3.4 | |
| Information Ordering | 3.4 | |
| Near Vision | 3.4 | |
| Problem Sensitivity | 3.3 | |
| Deductive Reasoning | 3.3 | |
| Inductive Reasoning | 3.3 | |
| Selective Attention | 3.3 | |
| Category Flexibility | 3.1 |
Transferable skills
| Social Perceptiveness | 3.4 | |
| Service Orientation | 3.3 | |
| Time Management | 3.3 | |
| Complex Problem Solving | 3.1 | |
| Coordination | 3.0 | |
| Persuasion | 3.0 | |
| Negotiation | 3.0 | |
| Instructing | 2.9 | |
| Management of Personnel Resources | 2.9 | |
| Judgment and Decision Making | 2.6 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
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.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 42.4% | |
| Associate's Degree (or other 2-year degree) | 33.5% | |
| Some College Courses | 5.9% | |
| Bachelor's Degree | 0.9% | |
| Master's Degree | 0.2% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Conventional | 6.0 | |
| Social | 4.1 | |
| Enterprising | 3.7 | |
| Investigative | 1.9 |
Interest areas
| Office Work | 5.8 | |
| Health Care Service | 3.0 | |
| Human Resources | 2.9 | |
| Personal Service | 2.8 | |
| Management/Administration | 2.6 | |
| Accounting | 2.4 | |
| Social Service | 2.3 | |
| Finance | 2.1 |
Work styles
| Dependability | 4.0 | |
| Attention to Detail | 3.0 | |
| Social Orientation | 2.2 | |
| Cooperation | 2.1 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $31,980 |
| 25th percentile | $37,380 |
| Median (50th) | $43,830 |
| 75th percentile | $50,440 |
| 90th percentile | $60,960 |
| People employed | 157,310 |
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 |
|---|---|---|
| Health Care and Social Assistance · Sector | 104,910 | $44,920 |
| Professional, Scientific, and Technical Services · Sector | 16,650 | $36,680 |
| Educational Services · Sector | 15,200 | $48,180 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 7,630 | $39,230 |
| Management of Companies and Enterprises · Sector | 5,250 | $45,190 |
| Finance and Insurance · Sector | 1,840 | $47,590 |
| Temporary Help Services · National industry | 1,790 | $43,440 |
| Outpatient Mental Health and Substance Abuse Centers · National industry | 1,440 | $43,250 |
| Residential Mental Health and Substance Abuse Facilities · National industry | 1,330 | $46,890 |
| Other Services (except Public Administration) · Sector | 1,310 | $46,080 |
| Services for the Elderly and Persons with Disabilities · National industry | 1,230 | $49,250 |
| Research and Development in the Social Sciences and Humanities · National industry | 760 | $44,150 |
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 |
|---|---|---|
| Research and Development in the Social Sciences and Humanities · National industry | 12.25× | 760 |
| Residential Mental Health and Substance Abuse Facilities · National industry | 5.04× | 1,330 |
| Outpatient Mental Health and Substance Abuse Centers · National industry | 4.56× | 1,440 |
| Health Care and Social Assistance · Sector | 4.45× | 104,910 |
| Offices of Mental Health Practitioners (except Physicians) · National industry | 2.03× | 500 |
| Management of Companies and Enterprises · Sector | 1.83× | 5,250 |
| Professional, Scientific, and Technical Services · Sector | 1.52× | 16,650 |
| Direct Health and Medical Insurance Carriers · National industry | 1.24× | 570 |
Related occupations
Part of the Healthcare & Human Services career cluster.
- Eligibility Interviewers, Government Programs · 43-4061.00 Compare →
- Patient Representatives · 29-2099.08 Compare →
- Office Clerks, General · 43-9061.00 Compare →
- Human Resources Assistants, Except Payroll and Timekeeping · 43-4161.00 Compare →
- Receptionists and Information Clerks · 43-4171.00 Compare →
- Medical Secretaries and Administrative Assistants · 43-6013.00 Compare →
- Secretaries and Administrative Assistants, Except Legal, Medical, and Executive · 43-6014.00 Compare →
- Customer Service Representatives · 43-4051.00 Compare →
- Correspondence Clerks · 43-4021.00 Compare →
- Health Information Technologists and Medical Registrars · 29-9021.00 Compare →
- Survey Researchers · 19-3022.00 Compare →
- Social Science Research Assistants · 19-4061.00 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 Interviewers, Except Eligibility and Loan — 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
Zoom out
On the global GenAI exposure gradient this work sits around the 92nd percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Interviewers, Except Eligibility and Loan show 78th-percentile AI task overlap — and about 15,800 annual U.S. openings
- Interviewers, Except Eligibility and Loan rank in the 78th 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 15,800 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 (-11.6%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $43,830, across about 157,310 U.S. workers.BLS OEWS (May 2024)
- Of the AI use actually observed for this work, 32% 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
Interviewers, Except Eligibility and Loan show 78th-percentile AI task overlap — and about 15,800 annual U.S. openings • Interviewers, Except Eligibility and Loan rank in the 78th 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 15,800 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 (-11.6%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $43,830, across about 157,310 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 32% 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 — "Interviewers, Except Eligibility and Loan". https://singulariki.com/roles/role-43-4111-00 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. "Interviewers, Except Eligibility and Loan." 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-43-4111-00
APA
Singulariki. (2026). Interviewers, Except Eligibility and Loan. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-43-4111-00
BibTeX
@misc{singulariki-role-43-4111-00,
title = {Interviewers, Except Eligibility and Loan},
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-43-4111-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.