Medium AI Risk Slow Growth

Special education teachers, middle school

SOC Code: 25-2057

Special education teachers, middle school carries a 36% AI exposure score (Medium automation risk), with a median annual wage of $64,880 and -1.9% projected employment growth from 2024 to 2034 (BLS), affecting approximately 94,800 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
36% Medium

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
-1.9%
2024–2034 (BLS)
-1,800 jobs
Median Annual Wage
$64,880
BLS May 2024
How wage figures are sourced →
The verdict

At 36% AI exposure, Special education teachers, middle school sits 1 points below the 37.2% average across 832 U.S. occupations - more exposed than 58% of them. Most of its core tasks still require human judgment.

36%
AI exposure
Top 42%
most exposed
-1.9%
Job growth 2024–34
$64,880
Median wage

Where Special education teachers, middle school sits among all occupations

AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.

AI exposure distribution - Special education teachers, middle school marked 1 occupations at 0–10% 1 0 43 occupations at 10–20% 43 10 184 occupations at 20–30% 184 20 332 occupations at 30–40% 332 30 158 occupations at 40–50% 158 40 64 occupations at 50–60% 64 50 29 occupations at 60–70% 29 60 15 occupations at 70–80% 15 70 5 occupations at 80–90% 5 80 1 occupations at 90–100% 1 90 AI exposure (%) →
Top 42% by AI exposure Higher AI exposure than 58% of all 832 occupations.

Special education teachers, middle school has ai exposure of 36%. Distribution: 1 occupations at 0-10%; 43 occupations at 10-20%; 184 occupations at 20-30%; 332 occupations at 30-40%; 158 occupations at 40-50%; 64 occupations at 50-60%; 29 occupations at 60-70%; 15 occupations at 70-80%; 5 occupations at 80-90%; 1 occupations at 90-100%.

Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.

Special education teachers, middle school vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Special education teachers, middle school is marked in rose; the top-left corner is the most future-proof.

Future-proofGrowing but exposedStable, lower-AIMost at risk25.4%28.9%32.5%36.1%39.6%-3.0%2.3%7.7%13.0%18.3%AI exposure (%) →Projected growth (%) →Special education teTeaching assistantsElementary school teSecondary school teaMiddle school teachePreschool teachersSubstitute teachersSelf-enrichment teacHealth specialties tInstructional coordiSpecial education teTutors

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

94,800
Employment 2024
93,000
Projected 2034
-1.9%
Change (%)
-1,800
Change (jobs)

Occupation Insight

Special education teachers, middle school (SOC 25-2057) carries an AI exposure score of 36%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an 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 economic context matters alongside the risk score. BLS counted approximately 94,800 workers in this occupation in 2024, and projects a -1.9% change through 2034 - a decline that often compounds with high AI exposure to create displacement headwinds. Median annual compensation stands at $64,880, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires Bachelor's degree, plus None of related experience.

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 Special education teachers, middle school. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
Bachelor's degree
Work Experience
None
On-the-Job Training
None

Top Tasks (O*NET)

  1. 1. Develop or write Individualized Education Programs (IEPs) for students.
  2. 2. Establish and enforce rules for behavior and policies and procedures to maintain order among students.
  3. 3. Develop and implement strategies to meet the needs of students with a variety of handicapping conditions.
  4. 4. Prepare materials and classrooms for class activities.
  5. 5. Instruct students in daily living skills required for independent maintenance and self-sufficiency, such as hygiene, safety, and food preparation.
  6. 6. Confer with parents or guardians, other teachers, counselors, and administrators to resolve students' behavioral and academic problems.
  7. 7. Coordinate placement of students with special needs into mainstream classes.
  8. 8. Confer with parents, administrators, testing specialists, social workers, and professionals to develop individual educational plans (IEPs) for students' educational, physical, and social development.
  9. 9. Modify the general education curriculum for students with disabilities, based upon a variety of instructional techniques and instructional technology.
  10. 10. Teach socially acceptable behavior, employing techniques such as behavior modification and positive reinforcement.

Key Skills Required

  • Active Listening
  • Speaking
  • Active Learning
  • Learning Strategies
  • Social Perceptiveness
  • Instructing
  • Reading Comprehension
  • Writing
  • Monitoring
  • Coordination

Knowledge Areas

  • English Language
  • Education and Training
  • Mathematics
  • Administrative
  • Customer and Personal Service
  • Psychology
  • Sociology and Anthropology
  • Public Safety and Security
  • Law and Government
  • Administration and Management

Frequently Asked Questions

Will AI replace Special education teachers, middle school?

Special education teachers, middle school 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 Special education teachers, middle school?

According to BLS Employment Projections 2024-2034, Special education teachers, middle school is projected to decline by 1.9% over the decade. Current employment stands at approximately 94,800 workers.

What skills are needed for Special education teachers, middle school?

Key skills for Special education teachers, middle school include Active Listening, Speaking, Active Learning, and others. Typical entry-level education is Bachelor's degree.

How much do Special education teachers, middle school earn?

The median annual wage for Special education teachers, middle school is $64,880, 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 Special education teachers, middle school?

The typical entry-level education for Special education teachers, middle school 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 Special education teachers, middle school?

Special education teachers, middle school 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

1.8
out of 5.0

Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.

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).

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial

Every figure on PlainWorkforce is rendered directly from BLS/O*NET source data, no number is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these figures, or report a data error. Data current as of BLS Employment Projections 2024-2034.