# Court, Municipal, and License Clerks

> Perform clerical duties for courts of law, municipalities, or governmental licensing agencies and bureaus. May prepare docket of cases to be called; secure information for judges and court; prepare draft agendas or bylaws for town or city council; answer official correspondence; keep fiscal records and accounts; issue licenses or permits; and record data, administer tests, or collect fees.

- **SOC code:** 43-4031.00
- **Canonical URL:** https://singulariki.com/roles/role-43-4031-00
- **Also known as:** City Clerk, Court Clerk, License Clerk, Town Clerk, City Recorder, License Specialist, Motor Vehicle Field Representative (MVFR), Motor Vehicle Licensing Clerk
- **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):
- Evaluate information on applications to verify completeness and accuracy and to determine whether applicants are qualified to obtain desired licenses.
- Perform administrative tasks, such as answering telephone calls, filing court documents, or maintaining office supplies or equipment.
- Verify the authenticity of documents, such as foreign identification or immigration documents.
- Record and edit the minutes of meetings and distribute to appropriate officials or staff members.
- Question applicants to obtain required information, such as name, address, or age, and record data on prescribed forms.
- Issue public notification of all official activities or meetings.
- Record and maintain all vital and fiscal records and accounts.
- Record case dispositions, court orders, or arrangements made for payment of court fees.
- Answer questions or provide advice to the public regarding licensing policies, procedures, or regulations.
- Prepare meeting agendas or packets of related information.
- Examine legal documents submitted to courts for adherence to laws or court procedures.
- Participate in the administration of municipal elections, such as preparation or distribution of ballots, appointment or training of election officers, or tabulation or certification of results.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Customer and Personal Service _(knowledge)_
- Administrative _(knowledge)_
- Law and Government _(knowledge)_
- English Language _(knowledge)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Active Listening _(essential_skill)_
- Speaking _(essential_skill)_
- Near Vision _(ability)_
- Written Comprehension _(ability)_
- Speech Recognition _(ability)_
- Administration and Management _(knowledge)_

**Skills in demand:**
- English Language _(Common Skill)_
- Active Listening _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Writing _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Inductive Reasoning _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft Word _(hot technology, in demand)_
- Adobe Acrobat _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Zoom _(hot technology)_
- Abilis CORIS Offender Management System
- Corel WordPerfect Office Suite
- Data Technologies Summit
- Email software

## AI exposure & outlook

- **AI task-overlap index:** 88th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 82nd percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 89th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 79th percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 45th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.0% growth (About average); 18.5k annual openings; 180.4k → 185.9k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $47,700; 170,010 employed.

## 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-43-4031-00_