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.
- Place children in foster or adoptive homes, institutions, or medical treatment centers.73
- Address legal issues, such as child abuse and discipline, assisting with hearings and providing testimony to inform custody arrangements.73
- Arrange for medical, psychiatric, and other tests that may disclose causes of difficulties and indicate remedial measures.72
- Evaluate personal characteristics and home conditions of foster home or adoption applicants.72
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.
- Develop and review service plans in consultation with clients and perform follow-ups assessing the quantity and quality of services provided.01
- Consult with parents, teachers, and other school personnel to determine causes of problems, such as truancy and misbehavior, and to implement solutions.02
- Counsel students whose behavior, school progress, or mental or physical impairment indicate a need for assistance, diagnosing students' problems and arranging for needed services.03
- Interview clients individually, in families, or in groups, assessing their situations, capabilities, and problems to determine what services are required to meet their needs.04
- Collect supplementary information needed to assist client, such as employment records, medical records, or school reports.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
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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.
