Share and intensity of work current AI systems can materially affect.
SOC 25-1194
Career and Technical Education Teachers, Postsecondary AI displacement risk
Career and technical education teachers train students in welding, healthcare, culinary, and other occupational skills. Their enrollment strengthens as students seek AI-resilient careers — the same disruption that pressures lecture disciplines pushes learners toward hands-on programs with equipment and employer pipelines.
Likely potential for exposed tasks to move to software after workflow integration.
The subject matter is the moat: supervising students on real equipment, administering performance tests, and maintaining industry partnerships are physical and relational work. AI tools help with lesson prep; the shop floor is the classroom.
Distribution
Where Career and Technical Education Teachers, Postsecondary sits across 620 tracked roles
Displacement pressure 22 — higher than 29% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
20 O*NET task statements matched to SOC 25-1194. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $63,820 (May 2025, US national). The latest BLS row matched SOC 25-1194.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Career and Technical Education Teachers, Postsecondary
SOC 25-1194 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 22/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Career and Technical Education Teachers, Postsecondary
The current evidence import matched 20 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks20
SOC25-1194
- Core task / ID 6446
Observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement.
- Core task / ID 6447
Present lectures and conduct discussions to increase students' knowledge and competence using visual aids, such as graphs, charts, videotapes, and slides.
- Core task / ID 6445
Supervise and monitor students' use of tools and equipment.
- Core task / ID 6448
Administer oral, written, or performance tests to measure progress and to evaluate training effectiveness.
- Core task / ID 6452
Provide individualized instruction and tutorial or remedial instruction.
- Core task / ID 6449
Prepare reports and maintain records, such as student grades, attendance rolls, and training activity details.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Supervise and monitor student use of tools and equipment
Exposure 22, automation 8%, augmentation 48%.
O*NET evidence: Supervise and monitor students' use of tools and equipment. (ID 6445)
Present lectures and conduct discussions
Exposure 50, automation 26%, augmentation 64%.
O*NET evidence: Present lectures and conduct discussions to increase students' knowledge and competence... (ID 6447)
Administer performance tests to evaluate training
Exposure 36, automation 17%, augmentation 54%.
O*NET evidence: Administer oral, written, or performance tests to measure progress and to evaluate trai... (ID 6448)
Develop curricula and plan course content
Exposure 50, automation 25%, augmentation 62%.
O*NET evidence: Develop curricula and plan course content and methods of instruction. (ID 6454)
TaskExposureAutomationAugmentation
Supervise and monitor student use of tools and equipment228%48%
Present lectures and conduct discussions5026%64%
Administer performance tests to evaluate training3617%54%
Develop curricula and plan course content5025%62%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
LowCTE Program Director
Training horizon: 6-12 months. Skill overlap 68. Wage preservation signal 118.
- Own program accreditation
- Build employer advisory boards
- Manage equipment budgets
role redesign
LowWorkforce Development Manager
Training horizon: 6-12 months. Skill overlap 64. Wage preservation signal 116.
- Design employer-customized training
- Measure placement outcomes
- Manage grant programs
Comparison guides
Compare the next move before you commit
6-12 months
Career and Technical Education Teachers, Postsecondary to CTE Program Director
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Career and Technical Education Teachers, Postsecondary into CTE Program Director.
6-12 months
Career and Technical Education Teachers, Postsecondary to Workforce Development Manager
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Career and Technical Education Teachers, Postsecondary into Workforce Development Manager.
What the AI risk score means for Career and Technical Education Teachers, Postsecondary
The displacement pressure score for Career and Technical Education Teachers, Postsecondary is 22. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Present lectures and conduct discussions carries 26% automation pressure, while Present lectures and conduct discussions carries 64% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $63,820 (May 2025, US national). Employment context: Trades instructor role with enrollment tailwinds. Typical education: Industry experience plus teaching credential; degree varies.
Wage vulnerability is 36, while transition feasibility is 70. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Low displacement pressure
- Trades enrollment grows on AI anxiety
- Shop supervision is the classroom
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Career and Technical Education Teachers, Postsecondary, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Technical instruction
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Equipment supervision
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Performance assessment
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Industry partnerships
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to CTE Program Director, such as own program accreditation.
- By 90 days, compare internal openings and external postings for CTE Program Director or Workforce Development Manager and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Career and Technical Education Teachers, Postsecondary
Will AI replace Career and Technical Education Teachers, Postsecondary?
Career and technical education teachers train students in welding, healthcare, culinary, and other occupational skills. Their enrollment strengthens as students seek AI-resilient careers — the same disruption that pressures lecture disciplines pushes learners toward hands-on programs with equipment and employer pipelines. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Career and Technical Education Teachers, Postsecondary work are most exposed to AI?
Present lectures and conduct discussions and Develop curricula and plan course content show the strongest automation pressure in this model. Present lectures and conduct discussions and Develop curricula and plan course content are better treated as AI-augmented work.
What should Career and Technical Education Teachers, Postsecondary learn next?
Start with Technical instruction, Equipment supervision, Performance assessment. The most practical adjacent paths in this model are CTE Program Director and Workforce Development Manager.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureOECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics