Interpreters and translators
SOC Code: 27-3091
Interpreters and translators carries a 53% AI exposure score (High automation risk), with a median annual wage of $59,440 and +1.7% projected employment growth from 2024 to 2034 (BLS), affecting approximately 75,300 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 53% AI exposure, Interpreters and translators sits 16 points above the 37.2% average across 832 U.S. occupations - more exposed than 90% of them. Most of its core tasks still require human judgment.
Career outlook score
36/100
Interpreters and translators, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage C- $59,440
Annual median wage, percentile rank vs all tracked occupations
- Projected growth D +1.7%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) F 53% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Interpreters and translators in the High band.
Credential × growth standing
Bachelor's band with mid-pack BLS pace
Interpreters and translators shares the Bachelor's gate with 178 peer occupations and lands in Slow growth (245 of 832). Neither the rarest nor the most crowded growth shelf - use wage and AI desks on this page for the differentiator.
Where Interpreters and translators sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Interpreters and translators sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
53% Higher than most higher than 90% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Interpreters and translators vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Interpreters and translators is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Interpreters and translators's High automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score in the 40–70% range indicates meaningful automation pressure on specific task categories, but the role as a whole still requires human judgment for coordination, exception handling, or client interaction.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 27-3091) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Interpreters and translators be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Interpreters and translators. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Follow ethical codes that protect the confidentiality of information.
- 2. Translate messages simultaneously or consecutively into specified languages, orally or by using hand signs, maintaining message content, context, and style as much as possible.
- 3. Listen to speakers' statements to determine meanings and to prepare translations, using electronic listening systems as necessary.
- 4. Compile terminology and information to be used in translations, including technical terms such as those for legal or medical material.
- 5. Adapt translations to students' cognitive and grade levels, collaborating with educational team members as necessary.
- 6. Refer to reference materials, such as dictionaries, lexicons, encyclopedias, and computerized terminology banks, as needed to ensure translation accuracy.
- 7. Check translations of technical terms and terminology to ensure that they are accurate and remain consistent throughout translation revisions.
- 8. Identify and resolve conflicts related to the meanings of words, concepts, practices, or behaviors.
- 9. Check original texts or confer with authors to ensure that translations retain the content, meaning, and feeling of the original material.
- 10. Compile information on content and context of information to be translated and on intended audience.
Key Skills Required
- Speaking
- Active Listening
- Reading Comprehension
- Writing
- Critical Thinking
- Monitoring
- Active Learning
- Social Perceptiveness
- Service Orientation
- Judgment and Decision Making
Knowledge Areas
- English Language
- Foreign Language
- Customer and Personal Service
- Education and Training
- Administrative
- Public Safety and Security
- Law and Government
- Computers and Electronics
- Communications and Media
- Psychology
Frequently Asked Questions
Will AI replace Interpreters and translators?
Interpreters and translators has an AI exposure score of 53%, indicating a high level of automation risk. Some tasks in this role can be augmented or partially automated by AI, but core responsibilities require human judgment.
What is the job outlook for Interpreters and translators?
According to BLS Employment Projections 2024-2034, Interpreters and translators is projected to grow by 1.7% over the decade. Current employment stands at approximately 75,300 workers.
What skills are needed for Interpreters and translators?
Key skills for Interpreters and translators include Speaking, Active Listening, Reading Comprehension, and others. Typical entry-level education is Bachelor's degree.
How much do Interpreters and translators earn?
The median annual wage for Interpreters and translators is $59,440, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Interpreters and translators?
The typical entry-level education for Interpreters and translators is Bachelor's degree. Employers generally expect None of related work experience. On-the-job training typically involves None. Requirements can vary by employer and specialization.
Which companies employ Interpreters and translators?
Interpreters and translators roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
High automation risk based on 10 analyzed tasks. A moderate share of tasks may be augmented by AI tools.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Interpreters and translators: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (53% here).
- Baggage porters and bellhops · AI exposure 53%
- Captains, mates, and pilots of water vessels · AI exposure 53%
- Financial risk specialists · AI exposure 53%
- Food science technicians · AI exposure 53%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (+1.7% here).
- Art, drama, and music teachers, postsecondary · growth +1.7%
- Clinical laboratory technologists and technicians · growth +1.7%
- Education administrators, postsecondary · growth +1.7%
- Industrial engineering technologists and technicians · growth +1.7%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 12 occupations with a comparable automation-risk profile.
What to do with this
Use Interpreters and translators' numbers above to compare, not just read in isolation.
- Compare Interpreters and translators side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).