Occupation · SOC 25-1124.00
Teach languages and literature courses in languages other than English. Includes teachers of American Sign Language (ASL). Includes both teachers primarily engaged in teaching and those who do a combination of teaching and research.
Also called: French Professor · Professor · Spanish Instructor · Spanish Professor · Assistant Professor · Associate Professor · Foreign Languages Professor · German Professor · Instructor · Modern Languages Professor · Adjunct Instructor · Adjunct Spanish Instructor
Job family: Educational Instruction and Library Occupations
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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.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
88th-percentile task overlap — yet about 1,900 openings a year (-0.2% projected, BLS), and observed AI use leans 6520% copilot, not hand-off (AEI) . What exposure means →
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.
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 | 90th | 1.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 65th | 0.8 | |
| AI assistant applicability (Microsoft) High | 95th | 0.3 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.3), 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.
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 and deliver lectures to undergraduate or graduate students on topics such as how to speak and write a foreign language and the cultural aspects of areas where a particular language is used. | 29.0% | |
| Plan, evaluate, and revise curricula, course content, course materials, and methods of instruction. | 17.8% | |
| Evaluate and grade students' class work, assignments, and papers. | 17.5% | |
| Compile, administer, and grade examinations, or assign this work to others. | 7.0% | |
| Initiate, facilitate, and moderate classroom discussions. | 6.6% | |
| Conduct research in a particular field of knowledge and publish findings in scholarly journals, books, or electronic media. | 5.5% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -0.2% by 2034 |
| Projected annual openings | 1,900 |
| Employment 2024 → 2034 | 26,400 → 26,400 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
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.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| University and Higher Education Teachers · 2310 | 37% | Minimal |
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.
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 | 65.2% working with AI · 32.5% 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) | 26.1% |
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 and deliver lectures to undergraduate or graduate students on topics such as how to speak and write a foreign language and the cultural aspects of areas where a particular language is used. | Learning | 55.2% |
| Evaluate and grade students' class work, assignments, and papers. | Validation | 25.7% |
| Advise students on academic and vocational curricula and on career issues. | Iteration | 23.7% |
| Provide professional consulting services to government or industry. | Iteration | 12.8% |
| Compile, administer, and grade examinations, or assign this work to others. | Directive | 10.6% |
| Plan, evaluate, and revise curricula, course content, course materials, and methods of instruction. | Iteration | 5.9% |
| Prepare course materials such as syllabi, homework assignments, and handouts. | Directive | 3.8% |
| Compile bibliographies of specialized materials for outside reading assignments. | Directive | 2.9% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Select and obtain materials and supplies such as textbooks. | 100.0% | |
| Maintain regularly scheduled office hours to advise and assist students. | 100.0% | |
| Collaborate with colleagues to address teaching and research issues. | 100.0% | |
| Participate in campus and community events. | 100.0% | |
| Write grant proposals to procure external research funding. | 100.0% | |
| Serve on academic or administrative committees that deal with institutional policies, departmental matters, and academic issues. | 100.0% |
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 and deliver lectures to undergraduate or graduate students on topics such as how to speak and write a foreign language and the cultural aspects of areas where a particular language is used. From: Prepare and deliver lectures to undergraduate or graduate students on topics such as how to speak and write a foreign language and the cultural aspects of areas where a particular language is used. · 55.2% of measured AI use · learning
Help me evaluate and grade students' class work, assignments, and papers. From: Evaluate and grade students' class work, assignments, and papers. · 25.7% of measured AI use · validation
Help me advise students on academic and vocational curricula and on career issues. From: Advise students on academic and vocational curricula and on career issues. · 23.7% of measured AI use · task iteration
Help me provide professional consulting services to government or industry. From: Provide professional consulting services to government or industry. · 12.8% of measured AI use · task iteration
All 25 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Foreign Language | 5.0 | |
| English Language | 4.4 | |
| Education and Training | 4.1 | |
| History and Archeology | 3.3 | |
| Philosophy and Theology | 3.3 | |
| Sociology and Anthropology | 3.1 | |
| Administrative | 3.0 | |
| Geography | 3.0 |
| Speech Clarity | 4.6 | |
| Oral Expression | 4.3 | |
| Oral Comprehension | 4.1 | |
| Written Comprehension | 4.0 | |
| Written Expression | 4.0 | |
| Speech Recognition | 4.0 | |
| Inductive Reasoning | 3.6 | |
| Deductive Reasoning | 3.4 | |
| Near Vision | 3.4 | |
| Problem Sensitivity | 3.3 | |
| Information Ordering | 3.0 | |
| Selective Attention | 3.0 | |
| Fluency of Ideas | 2.9 | |
| Originality | 2.9 | |
| Category Flexibility | 2.9 | |
| Memorization | 2.9 |
| Speaking | 4.1 | |
| Reading Comprehension | 4.0 | |
| Active Listening | 4.0 | |
| Writing | 4.0 | |
| Learning Strategies | 4.0 | |
| Active Learning | 3.9 | |
| Critical Thinking | 3.8 | |
| Monitoring | 3.6 |
| Instructing | 4.0 | |
| Complex Problem Solving | 3.5 | |
| Judgment and Decision Making | 3.5 | |
| Social Perceptiveness | 3.3 | |
| Coordination | 3.0 | |
| Time Management | 3.0 | |
| Service Orientation | 2.9 | |
| Persuasion | 2.8 |
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 43.
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.
What to study: Education , Foreign Languages, Literatures, and Linguistics , Multi/Interdisciplinary Studies . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Doctoral Degree | 73.4% | |
| Master's Degree | 17.8% | |
| Bachelor's Degree | 8.7% |
The interests and personal qualities O*NET associates with people who do this work.
| Social | 7.0 | |
| Investigative | 4.5 | |
| Artistic | 4.1 | |
| Conventional | 3.5 | |
| Enterprising | 2.5 |
| Teaching/Education | 6.8 | |
| Humanities | 6.3 | |
| Public Speaking | 5.7 | |
| Social Science | 5.0 | |
| Professional Advising | 4.6 | |
| Creative Writing | 3.4 | |
| Social Service | 3.0 |
| Dependability | 6.0 | |
| Attention to Detail | 5.0 | |
| Intellectual Curiosity | 4.0 | |
| Cooperation | 3.0 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $47,090 |
| 25th percentile | $59,790 |
| Median (50th) | $77,010 |
| 75th percentile | $101,680 |
| 90th percentile | $134,960 |
| People employed | 21,170 |
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 | 21,090 | $77,060 |
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 |
|---|---|---|
| Educational Services · Sector | 11.26× | 21,090 |
Part of the Education career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Foreign Language and Literature Teachers, Postsecondary — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 70th percentile of 427 international occupations.
Foreign Language and Literature Teachers, Postsecondary show 88th-percentile AI task overlap — and about 1,900 annual U.S. openings
Foreign Language and Literature Teachers, Postsecondary show 88th-percentile AI task overlap — and about 1,900 annual U.S. openings • Foreign Language and Literature Teachers, Postsecondary rank in the 88th 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 1,900 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 (-0.2%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $77,010, across about 21,170 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 65% 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 — "Foreign Language and Literature Teachers, Postsecondary". https://singulariki.com/roles/role-25-1124-00 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.
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.
Singulariki. "Foreign Language and Literature Teachers, Postsecondary." 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; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-25-1124-00
Singulariki. (2026). Foreign Language and Literature Teachers, Postsecondary. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-25-1124-00
@misc{singulariki-role-25-1124-00,
title = {Foreign Language and Literature Teachers, Postsecondary},
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; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-25-1124-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.