Train personnel.

Train personnel. is a detailed work activity in O*NET — a concrete unit of work shared across 12 occupations and seen in 13 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 13 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 7 (54%) 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 0.004% 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.

• Provide assistance in the training and orientation of new cashiers. · Gambling Cage Workers · importance 4.4 · no direct exposure
• Provide employees with guidance in handling difficult or complex problems or in resolving escalated complaints or disputes. · First-Line Supervisors of Office and Administrative Support Workers · importance 4.3 · exposure with tools
• Train new workers. · Postal Service Mail Sorters, Processors, and Processing Machine Operators · importance 4.0 · no direct exposure
• Train or instruct employees in job duties or company policies or arrange for training to be provided. · First-Line Supervisors of Office and Administrative Support Workers · importance 4.0 · exposure with tools
• Train other workers or coordinate their work, as necessary. · Court, Municipal, and License Clerks · importance 3.9 · no direct exposure
• Provide consultation or training to volunteers or staff on topics, such as guest relations, patients' rights, or medical issues. · Patient Representatives · importance 3.9 · exposure with tools
• Train police officers in dog handling and training techniques for tracking, crowd control, and narcotics and bomb detection. · Animal Control Workers · importance 3.6 · no direct exposure
• Train and supervise subordinates and other staff. · Procurement Clerks · importance 3.5 · no direct exposure
• Supervise and train other clerical staff and arrange for employee training by scheduling training or organizing training material. · Executive Secretaries and Executive Administrative Assistants · importance 3.4 · exposure with tools
• Train and assist staff with computer usage. · Secretaries and Administrative Assistants, Except Legal, Medical, and Executive · importance 3.4 · direct LLM exposure
• Train other staff members to perform work activities, such as using computer applications. · Office Clerks, General · importance 3.3 · no direct exposure
• Train bioinformatics staff or researchers in the use of databases. · Bioinformatics Technicians · importance 3.1 · direct LLM exposure
• Arrange for in-house and external training activities. · Human Resources Assistants, Except Payroll and Timekeeping · importance 2.9 · exposure with tools

Occupations that perform this

• Gambling Cage Workers
• First-Line Supervisors of Office and Administrative Support Workers
• Postal Service Mail Sorters, Processors, and Processing Machine Operators
• Court, Municipal, and License Clerks
• Patient Representatives
• Animal Control Workers
• Procurement Clerks
• Executive Secretaries and Executive Administrative Assistants
• Secretaries and Administrative Assistants, Except Legal, Medical, and Executive
• Office Clerks, General
• Bioinformatics Technicians
• Human Resources Assistants, Except Payroll and Timekeeping

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-personnel,
  title  = {Train personnel.},
  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-personnel}
}