Train customers in the use of products.
Detailed work activity
Train customers in the use of products. is a detailed work activity in O*NET — a concrete unit of work shared across 6 occupations and seen in 6 occupation-specific tasks. It rolls up into the broader work activity Train others to use equipment or products. 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 6 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 3 (50%) 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 0.002% 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.
- Advise customers concerning equipment operation, maintenance, or programming. · Computer, Automated Teller, and Office Machine Repairers · importance 4.3 · direct LLM exposure
- Show customers how to maintain equipment. · Outdoor Power Equipment and Other Small Engine Mechanics · importance 4.2 · no direct exposure
- Instruct customers regarding operation and care of appliances, and provide information such as emergency service numbers. · Home Appliance Repairers · importance 4.1 · direct LLM exposure
- Instruct customers on the safe and proper use of equipment. · Audiovisual Equipment Installers and Repairers · importance 4.0 · no direct exposure
- Train end-users, distributors, installers, or other technicians in wind commissioning, testing, or other technical procedures. · Wind Turbine Service Technicians · importance 3.8 · no direct exposure
- Advise customers on proper installation of valves or regulators and related equipment. · Control and Valve Installers and Repairers, Except Mechanical Door · importance 3.4 · exposure with tools
Occupations that perform this
- Computer, Automated Teller, and Office Machine Repairers
- Outdoor Power Equipment and Other Small Engine Mechanics
- Home Appliance Repairers
- Audiovisual Equipment Installers and Repairers
- Wind Turbine Service Technicians
- Control and Valve Installers and Repairers, Except Mechanical Door
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.
Cite this page
Singulariki. "Train customers in the use of products.." Singulariki: a source-backed encyclopedia of work. Built from 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. https://singulariki.com/detailed-activities/train-customers-in-the-use-of-products
Singulariki. (2026). Train customers in the use of products.. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/detailed-activities/train-customers-in-the-use-of-products
@misc{singulariki-train-customers-in-the-use-of-products,
title = {Train customers in the use of products.},
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-customers-in-the-use-of-products}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.