Computer science teachers, postsecondary
SOC Code: 25-1021
Computer science teachers, postsecondary carries a 36% AI exposure score (Medium automation risk), with a median annual wage of $96,690 and +5.3% projected employment growth from 2024 to 2034 (BLS), affecting approximately 44,800 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 36% AI exposure, Computer science teachers, postsecondary sits 1 points below the 37.2% average across 832 U.S. occupations - more exposed than 56% of them. Most of its core tasks still require human judgment.
Career outlook score
70/100
Computer science teachers, postsecondary, 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 A $96,690
Annual median wage, percentile rank vs all tracked occupations
- Projected growth B+ +5.3%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) D 36% 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 Computer science teachers, postsecondary in the Medium band.
Credential × growth standing
Graduate credential among the thinner entry shelves
Computer science teachers, postsecondary is in the Graduate band (113 of 832) with BLS pace Average (378/832). Graduate entry is a minority shelf - pairing it with average growth is the standing that separates this SOC from bachelor-dominated neighbors.
Where Computer science teachers, postsecondary sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Computer science teachers, postsecondary sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
36% Around the middle lower than 44% 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.
Computer science teachers, postsecondary vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Computer science teachers, postsecondary 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
Computer science teachers, postsecondary's Medium 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 below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.
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 25-1021) 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 Computer science teachers, postsecondary 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 Computer science teachers, postsecondary. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Prepare course materials, such as syllabi, homework assignments, and handouts.
- 2. Compile, administer, and grade examinations or assign this work to others.
- 3. Prepare and deliver lectures to undergraduate or graduate students on topics such as programming, data structures, and software design.
- 4. Evaluate and grade students' class work, laboratory work, assignments, and papers.
- 5. Direct research of other teachers or of graduate students working for advanced academic degrees.
- 6. Maintain student attendance records, grades, and other required records.
- 7. Supervise undergraduate or graduate teaching, internship, and research work.
- 8. Keep abreast of developments in the field by reading current literature, talking with colleagues, and participating in professional conferences.
- 9. Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction.
- 10. Conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media.
Key Skills Required
- Instructing
- Reading Comprehension
- Writing
- Speaking
- Active Listening
- Critical Thinking
- Active Learning
- Learning Strategies
- Judgment and Decision Making
- Monitoring
Knowledge Areas
- Computers and Electronics
- Education and Training
- English Language
- Customer and Personal Service
- Mathematics
- Engineering and Technology
- Administration and Management
- Administrative
- Design
- Public Safety and Security
Frequently Asked Questions
Will AI replace Computer science teachers, postsecondary?
Computer science teachers, postsecondary has an AI exposure score of 36%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.
What is the job outlook for Computer science teachers, postsecondary?
According to BLS Employment Projections 2024-2034, Computer science teachers, postsecondary is projected to grow by 5.3% over the decade. Current employment stands at approximately 44,800 workers.
What skills are needed for Computer science teachers, postsecondary?
Key skills for Computer science teachers, postsecondary include Instructing, Reading Comprehension, Writing, and others. Typical entry-level education is Doctoral or professional degree.
How much do Computer science teachers, postsecondary earn?
The median annual wage for Computer science teachers, postsecondary is $96,690, 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 Computer science teachers, postsecondary?
The typical entry-level education for Computer science teachers, postsecondary is Doctoral or professional 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 Computer science teachers, postsecondary?
Computer science teachers, postsecondary 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
Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Computer science teachers, postsecondary: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (36% here).
- Amusement and recreation attendants · AI exposure 36%
- Communications teachers, postsecondary · AI exposure 36%
- Computer network support specialists · AI exposure 36%
- Computer numerically controlled tool operators · AI exposure 36%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (+5.3% here).
- Compensation, benefits, and job analysis specialists · growth +5.3%
- First-line supervisors of construction trades and extraction workers · growth +5.3%
- Food processing workers, all other · growth +5.3%
- Motorcycle mechanics · growth +5.3%
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 57 occupations with a comparable automation-risk profile.
What to do with this
Use Computer science teachers, postsecondary's numbers above to compare, not just read in isolation.
- Compare Computer science teachers, postsecondary 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).