How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Prepare and maintain all required treatment records and reports.71
- Gather information about community mental health needs or resources that could be used in conjunction with therapy.71
- Develop and implement treatment plans based on clinical experience and knowledge.70
- Fill out and maintain client-related paperwork, including federal- and state-mandated forms, client diagnostic records, and progress notes.66
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Maintain confidentiality of records relating to clients' treatment.01
- Prepare and maintain all required treatment records and reports.02
- Encourage clients to express their feelings and discuss what is happening in their lives, helping them to develop insight into themselves or their relationships.03
- Fill out and maintain client-related paperwork, including federal- and state-mandated forms, client diagnostic records, and progress notes.04
- Guide clients in the development of skills or strategies for dealing with their problems.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Mental Health and Substance Abuse Social Workers
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Related work
Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
