Train others on work processes.

Train others on work processes. is a detailed work activity in O*NET — a concrete unit of work shared across 9 occupations and seen in 10 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 10 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 4 (40%) 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 1 of these tasks, with a mean mapped-usage share of 0.002% 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.

• Hire, train, and direct staff members who develop design concepts into art layouts or who prepare layouts for printing. · Art Directors · importance 4.0 · exposure with tools
• Train workers in use of equipment, such as switchers, cameras, monitors, microphones, and lights. · Media Technical Directors/Managers · importance 4.0 · no direct exposure
• Supervise or train staff members on daily tasks, such as visual merchandising. · Merchandise Displayers and Window Trimmers · importance 3.9 · no direct exposure
• Train and supervise other translators or interpreters. · Interpreters and Translators · importance 3.8 · direct LLM exposure
• Instruct trainees in use of television production equipment, filming of events, and copying and editing graphics or sound onto videotape. · Broadcast Technicians · importance 3.8 · no direct exposure
• Instruct sales staff in color coordination of clothing racks or counter displays. · Merchandise Displayers and Window Trimmers · importance 3.7 · exposure with tools
• Educate staff in the use of mathematical models. · Operations Research Analysts · importance 3.6 · exposure with tools
• Conduct training sessions on selection, use, and design of audio-visual materials and on operation of presentation equipment. · Audio and Video Technicians · importance 3.1 · no direct exposure
• Conduct classes or demonstrations, or train other workers. · Floral Designers · importance 3.1 · no direct exposure
• Teach writing classes. · Poets, Lyricists and Creative Writers · importance 2.8 · no direct exposure

Occupations that perform this

• Art Directors
• Media Technical Directors/Managers
• Merchandise Displayers and Window Trimmers
• Interpreters and Translators
• Broadcast Technicians
• Operations Research Analysts
• Audio and Video Technicians
• Floral Designers
• Poets, Lyricists and Creative Writers

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-others-on-work-processes,
  title  = {Train others on work processes.},
  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-others-on-work-processes}
}