Train staff members.

Train staff members. is a detailed work activity in O*NET — a concrete unit of work shared across 9 occupations and seen in 9 occupation-specific tasks. It rolls up into the broader work activity Train others on operational or work procedures. in Training and Teaching Others .

Detailed work activities are the most granular shared layer in O*NET's work-activity hierarchy (Generalized → Intermediate → Detailed → occupation-specific task). The figures below describe how this activity shows up across the economy and what independent studies measure about AI and this kind of work — not a prediction that the work will be automated.

AI exposure

Of the 8 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 3 (38%) are flagged as directly exposed to language models (E1) or exposed via model-powered tools (E2).

The Anthropic Economic Index observes real AI use on 2 of these tasks, with a mean mapped-usage share of 0.006% per task.

Exposure estimates overlap with model capabilities — whether a model could speed the task up — not whether the work will be done by software. Observed AI use is augmentation and assistance today, not jobs replaced.

Member tasks

Occupation-specific tasks O*NET maps to this detailed work activity, most important first.

• Plan and conduct teacher training programs and conferences dealing with new classroom procedures, instructional materials and equipment, and teaching aids. · Instructional Coordinators · importance 4.1 · no direct exposure
• Supervise and train interns, clinicians in training, and other counselors. · Clinical and Counseling Psychologists · importance 3.8 · no direct exposure
• Direct and train library staff in duties, such as receiving, shelving, researching, cataloging, and equipment use. · Librarians and Media Collections Specialists · importance 3.7 · exposure with tools
• Train and supervise curatorial, fiscal, technical, research, and clerical staff, as well as volunteers or interns. · Curators · importance 3.6 · no direct exposure
• Train other staff, volunteers, or student assistants and schedule and supervise their work. · Library Technicians · importance 3.6 · no direct exposure
• Train and assist tutors and community literacy volunteers. · Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors · importance 3.5 · no direct exposure
• Recruit, train, and supervise department personnel, such as faculty and student writing instructors. · English Language and Literature Teachers, Postsecondary · importance 3.4 · exposure with tools
• Advise and instruct teachers employed in school systems by providing activities, such as in-service seminars. · Education Teachers, Postsecondary · importance 2.9 · exposure with tools
• Train staff on park programs. · 19-1031.03

Occupations that perform this

• Instructional Coordinators
• Clinical and Counseling Psychologists
• Librarians and Media Collections Specialists
• Curators
• Library Technicians
• Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors
• English Language and Literature Teachers, Postsecondary
• Education Teachers, Postsecondary
• 19-1031.03

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-train-staff-members,
  title  = {Train staff members.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/detailed-activities/train-staff-members}
}