Low AI Risk Fast Growth

Mental health and substance abuse social workers

SOC Code: 21-1023

Mental health and substance abuse social workers carries a 18% AI exposure score (Low automation risk), with a median annual wage of $60,060 and +9.7% projected employment growth from 2024 to 2034 (BLS), affecting approximately 136,800 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
18% Low

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

Projected Growth
+9.7%
2024–2034 (BLS)
+13,300 jobs
Median Annual Wage
$60,060
BLS May 2024
How wage figures are sourced →
The verdict

At 18% AI exposure, Mental health and substance abuse social workers sits 19 points below the 37.2% average across 832 U.S. occupations - more exposed than 4% of them. It ranks among the more AI-resilient roles in the dataset.

18%
AI exposure
4th
percentile
+9.7%
Job growth 2024–34
$60,060
Median wage

Where Mental health and substance abuse social workers 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 - Mental health and substance abuse social workers 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 96% by AI exposure Higher AI exposure than 4% of all 832 occupations.

Mental health and substance abuse social workers has ai exposure of 18%. 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.

Mental health and substance abuse social workers vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Mental health and substance abuse social workers is marked in rose; the top-left corner is the most future-proof.

Future-proofGrowing but exposedStable, lower-AIMost at risk16.9%23.2%29.5%35.8%42.1%0%4.4%8.8%13.2%17.6%AI exposure (%) →Projected growth (%) →Substance abuseSocialChildEducationalClergyHealthcare social woDirectorsMental healthCommunityProbation officersRehabilitation couns

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

Employment Projections

136,800
Employment 2024
150,100
Projected 2034
+9.7%
Change (%)
+13,300
Change (jobs)

Occupation Insight

Mental health and substance abuse social workers (SOC 21-1023) carries an AI exposure score of 18%, placing it in the Low 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 136,800 workers in this occupation in 2024, and projects a +9.7% change through 2034 - modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $60,060, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires Master'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 Mental health and substance abuse social workers. 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
Master's degree
Work Experience
None
On-the-Job Training
Internship/residency

Top Tasks (O*NET)

  1. 1. Counsel clients in individual or group sessions to assist them in dealing with substance abuse, mental or physical illness, poverty, unemployment, or physical abuse.
  2. 2. Collaborate with counselors, physicians, or nurses to plan or coordinate treatment, drawing on social work experience and patient needs.
  3. 3. Monitor, evaluate, and record client progress with respect to treatment goals.
  4. 4. Interview clients, review records, conduct assessments, or confer with other professionals to evaluate the mental or physical condition of clients or patients.
  5. 5. Supervise or direct other workers who provide services to clients or patients.
  6. 6. Modify treatment plans according to changes in client status.
  7. 7. Assist clients in adhering to treatment plans, such as setting up appointments, arranging for transportation to appointments, or providing support.
  8. 8. Educate clients or community members about mental or physical illness, abuse, medication, or available community resources.
  9. 9. Counsel or aid family members to assist them in understanding, dealing with, or supporting the client or patient.
  10. 10. Increase social work knowledge by reviewing current literature, conducting social research, or attending seminars, training workshops, or classes.

Key Skills Required

  • Social Perceptiveness
  • Active Listening
  • Speaking
  • Reading Comprehension
  • Critical Thinking
  • Monitoring
  • Coordination
  • Service Orientation
  • Complex Problem Solving
  • Writing

Knowledge Areas

  • Therapy and Counseling
  • Psychology
  • English Language
  • Customer and Personal Service
  • Education and Training
  • Sociology and Anthropology
  • Public Safety and Security
  • Medicine and Dentistry
  • Philosophy and Theology
  • Administration and Management

Frequently Asked Questions

Will AI replace Mental health and substance abuse social workers?

Mental health and substance abuse social workers has an AI exposure score of 18%, indicating a low 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 Mental health and substance abuse social workers?

According to BLS Employment Projections 2024-2034, Mental health and substance abuse social workers is projected to grow by 9.7% over the decade. Current employment stands at approximately 136,800 workers.

What skills are needed for Mental health and substance abuse social workers?

Key skills for Mental health and substance abuse social workers include Social Perceptiveness, Active Listening, Speaking, and others. Typical entry-level education is Master's degree.

How much do Mental health and substance abuse social workers earn?

The median annual wage for Mental health and substance abuse social workers is $60,060, 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 Mental health and substance abuse social workers?

The typical entry-level education for Mental health and substance abuse social workers is Master's degree. Employers generally expect None of related work experience. On-the-job training typically involves Internship/residency. Requirements can vary by employer and specialization.

Which companies employ Mental health and substance abuse social workers?

Mental health and substance abuse social workers 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

0.9
out of 5.0

Low 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.