Headline risk
36%
High RiskCareer/technical education teachers, middle school
United States AI Work Index tracks this occupation on the shared structural baseline and then layers on local demand resilience, wages, and confidence.
Why This Score
Share of job tasks that overlap with current AI capabilities
Median annual wage
Projected employment change over 10 years
Typical preparation needed for this occupation
Occupation profile
Teach occupational, vocational, career, or technical subjects to students at the middle, intermediate, or junior high school level.
Task evidence
97% weighted task match · 20% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 63,620
Employment 2024
14.0K
Projected Change (2024–34)
-2.0%
Openings (2024–34)
0.9K
Wage distribution
Demand outlook
Overall employment of career and technical education teachers is projected to grow 1 percent from 2024 to 2034, decline.
Role Profile
Tasks
- 1. Instruct students individually and in groups, using various teaching methods, such as lectures, discussions, and demonstrations. AI use: 0%
- 2. Prepare materials and classrooms for class activities. AI use: 0%
- 3. Adapt teaching methods and instructional materials to meet students' varying needs and interests. AI use: 82%
- 4. Establish and enforce rules for behavior and procedures for maintaining order among students. AI use: 0%
- 5. Establish clear objectives for all lessons, units, and projects, and communicate those objectives to students. AI use: 0%
- 6. Prepare students for later educational experiences by encouraging them to explore learning opportunities and to persevere with challenging tasks. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 43.4 · 3.5M employed
Under 25: 6% · 25–54: 74% · 55+: 20%
Related
Systems Analyst →
Estimated modern role scored with US data
Business Analyst →
Estimated modern role scored with US data
Cloud Architect →
Estimated modern role scored with US data
Solutions Engineer →
Estimated modern role scored with US data
Technical Product Manager →
Estimated modern role scored with US data
AI Product Manager →
Estimated modern role scored with US data
Data Analyst →
Estimated modern role scored with US data
Data Architect →
Estimated modern role scored with US data
Product Manager →
Estimated modern role scored with US data
Sales Engineer →
Estimated modern role scored with US data
Startup CTO →
Estimated modern role scored with US data
Technical Writer →
Estimated modern role scored with US data
AI Engineer →
Estimated modern role scored with US data
QA Engineer →
Estimated modern role scored with US data
RevOps Manager →
Estimated modern role scored with US data
Startup Founder / CEO →
Estimated modern role scored with US data
Source coverage
11/11 source families · O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Mapping quality
major_group_fallback · employment series present
Narrative & sources
Career and technical education teachers instruct students in various technical and vocational subjects, such as auto repair, healthcare, and culinary arts.
Most career and technical education teachers work in middle, high, and postsecondary schools, such as 2-year colleges. Others work in technical, trade, and business schools. Although they generally work during school hours, some teach evening or weekend classes.
Career and technical education teachers typically need at least a bachelor’s degree and work experience in the subject that they teach. Public school teachers may be required to have a state-issued teaching certification or license.
The median annual wage for career and technical education teachers was $62,910 in May 2024.
Overall employment of career and technical education teachers is projected to grow 1 percent from 2024 to 2034, decline.
Published limitations
This page shows the local country layer, not realised individual job outcomes. The global structural baseline is shared across countries; only the local demand and wage layer changes here.
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.