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Singulariki

Legislators

Occupation · SOC 11-1031.00

Develop, introduce, or enact laws and statutes at the local, tribal, state, or federal level. Includes only workers in elected positions.

Also called: Alderman · Assembly Member · Assembly Person · Assemblyman · Assemblywoman · City Alderman · City Council Member · City Councilman · Congress Member · Congressional Representative · Congressman · Congresswoman

Job family: Management Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-11-1031-00/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.

  • Prepare drafts of amendments, government policies, laws, rules, regulations, budgets, programs and procedures. · 0.5%
  • Confer with colleagues to formulate positions and strategies pertaining to pending issues. · 0.4%
See collaboration patterns →

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.

  • Confer with colleagues to formulate positions and strategies pertaining to pending issues. · 100.0% need a human
  • Prepare drafts of amendments, government policies, laws, rules, regulations, budgets, programs and procedures. · 97.9% need a human
  • Determine campaign strategies for media advertising, positions on issues, and public appearances. · 92.1% need a human
See the boundary tasks →

73rd-percentile task overlap — yet about 2,200 openings a year (+3.4% projected, BLS), and observed AI use leans 4426% 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
LLM task exposure, γ (OpenAI / Eloundou) Moderate 61st 0.8
AI assistant applicability (Microsoft) High 84th 0.3

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.4), 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.

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.

Prepare drafts of amendments, government policies, laws, rules, regulations, budgets, programs and procedures. 1.3%
Determine campaign strategies for media advertising, positions on issues, and public appearances. 0.4%
Represent their government at local, national, and international meetings and conferences. 0.3%
Write, prepare, and deliver statements for the Congressional Record. 0.2%
Represent their parties in negotiations with political executives or members of other parties, and when speaking with the media. 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 About average · +3.4% by 2034
Projected annual openings 2,200
Employment 2024 → 2034 27,700 → 28,600

“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 2 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

27% mean task exposure (2025)
51st percentile of 427 placed occupations
+0 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Legislators · 1111 31% Not exposed
Traditional Chiefs and Heads of Villages · 1113 23% 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 44.3% working with AI · 18.0% handed to AI
Most common way people use AI here Iteration · you and AI go back and forth
Typical AI autonomy 4.0 / 5 · higher = AI acts more independently
Used for work (vs. personal / coursework) 57.4%

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
Prepare drafts of amendments, government policies, laws, rules, regulations, budgets, programs and procedures. Iteration 0.5%
Determine campaign strategies for media advertising, positions on issues, and public appearances. 0.4%
Confer with colleagues to formulate positions and strategies pertaining to pending issues. Iteration 0.4%

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.

Confer with colleagues to formulate positions and strategies pertaining to pending issues. 100.0%
Prepare drafts of amendments, government policies, laws, rules, regulations, budgets, programs and procedures. 97.9%
Determine campaign strategies for media advertising, positions on issues, and public appearances. 92.1%

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 prepare drafts of amendments, government policies, laws, rules, regulations, budgets, programs and procedures.

    From: Prepare drafts of amendments, government policies, laws, rules, regulations, budgets, programs and procedures. · 0.5% of measured AI use · task iteration

  • Help me determine campaign strategies for media advertising, positions on issues, and public appearances.

    From: Determine campaign strategies for media advertising, positions on issues, and public appearances. · 0.4% of measured AI use

  • Help me confer with colleagues to formulate positions and strategies pertaining to pending issues.

    From: Confer with colleagues to formulate positions and strategies pertaining to pending issues. · 0.4% of measured AI use · task iteration

Tasks

All 30 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

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

Example Category
Adobe Acrobat Document management software Hot technology
Cisco Webex Video conferencing software Hot technology
Microsoft Access Data base user interface and query software Hot technology
Microsoft Excel Spreadsheet software Hot technology
Microsoft Office software Office suite software Hot technology
Microsoft Outlook Electronic mail software Hot technology
Microsoft SharePoint Document management software Hot technology
Microsoft SQL Server Data base user interface and query software Hot technology
Microsoft Visual Basic Development environment software Hot technology
Microsoft Word Word processing software Hot technology
Structured query language SQL Data base user interface and query software Hot technology
Adobe FrameMaker Desktop publishing software
Antenna House Desktop publishing software
Apple iWork Keynote Presentation software
Apple iWork Pages Word processing software
Apple Numbers for Mac Spreadsheet software
Cisco AnyConnect Access software
Corel WordPerfect Office Suite Office suite software
GoodReader Word processing software
iAnnotate Word processing software
IBM Domino Communications server software
Legislative Automative Workflow System LAWS Data base user interface and query software
LogMeIn GoToMeeting Video conferencing software
Mapping software Map creation software
Meeting scheduling software Calendar and scheduling software
Microsoft Exchange Electronic mail software
Penultimate Word processing software
PTC Arbortext Desktop publishing software
Rocket/Folio NXT Desktop publishing software
Web browser software Internet browser software
Windows Media Player Music or sound editing software
XMetaL Author Word processing software

How to get in

Job zone
Zone 4 — Job Zone Four: Considerable Preparation Needed
Education
Most of these occupations require a four-year bachelor's degree, but some do not.
Typical entry-level education
Bachelor's degree · BLS, the typical path — not a requirement
Related experience
A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
Preparation level
SVP (7.0 to < 8.0) — total schooling plus on-the-job experience.

What to study: Public Administration and Social Service Professions . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Work styles

Achievement Orientation 10.0
Social Orientation 9.0
Self-Control 8.0
Stress Tolerance 7.0
Perseverance 6.0
Adaptability 5.0
Leadership Orientation 4.0

Interest areas

Politics 7.0
Public Speaking 6.1
Law 5.5
Management/Administration 5.1
Business Initiatives 4.0
Social Science 3.4

Career interests (Holland / RIASEC)

Enterprising 5.5
Social 3.7
Conventional 3.6

Wages & employment

U.S. · annual wages (BLS OEWS)

$20k10th$29k25th$45kMedian$80k75th$138k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
28k202429k2034 (proj.)+3.4% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $20,380
25th percentile $29,120
Median (50th) $44,810
75th percentile $80,350
90th percentile $137,820
People employed 26,510

Part of the Public Service & Safety career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Legislators sits at the 73rd percentile of AI task-overlap and the 19th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Legislators Patient Representatives Labor Relations Specialists Equal Opportunity Representatives and Officers Judicial Law Clerks Education Administrators, Postsecondary Administrative Law Judges, Adjudicators, and Hearing Officers Chief Executives Executive Secretaries and Executive Administrative Assistants Public Relations Specialists AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

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 Legislators — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 51st percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Legislators show 73rd-percentile AI task overlap — and about 2,200 annual U.S. openings

  • Legislators rank in the 73rd 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 2,200 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 about average (+3.4%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $44,810, across about 26,510 U.S. workers.BLS OEWS (May 2024)
  • Of the AI use actually observed for this work, 44% 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
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Legislators show 73rd-percentile AI task overlap — and about 2,200 annual U.S. openings

• Legislators rank in the 73rd 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 2,200 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 about average (+3.4%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $44,810, across about 26,510 U.S. workers. (BLS OEWS (May 2024))
• Of the AI use actually observed for this work, 44% 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 — "Legislators". https://singulariki.com/roles/role-11-1031-00
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.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Legislators." 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; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022. Accessed June 7, 2026. https://singulariki.com/roles/role-11-1031-00

APA

Singulariki. (2026). Legislators. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-11-1031-00

BibTeX
@misc{singulariki-role-11-1031-00,
  title  = {Legislators},
  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; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-11-1031-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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