Evaluate project designs to determine adequacy or feasibility.

Evaluate project designs to determine adequacy or feasibility. is a detailed work activity in O*NET — a concrete unit of work shared across 5 occupations and seen in 6 occupation-specific tasks. It rolls up into the broader work activity Evaluate project feasibility. in Judging the Qualities of Objects, Services, or People .

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, 6 (100%) 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 0.003% 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.

• Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy. · Statisticians · importance 4.7 · direct LLM exposure
• Test and evaluate hardware and software to determine efficiency, reliability, or compatibility with existing systems. · Telecommunications Engineering Specialists · importance 3.9 · direct LLM exposure
• Evaluate network designs to determine whether customer requirements are met efficiently and effectively. · Computer Network Architects · importance 3.7 · exposure with tools
• Review and approve all systems charts and programs prior to their implementation. · Computer and Information Systems Managers · importance 3.7 · direct LLM exposure
• Review designs, codes, test plans, or documentation to ensure quality. · Data Warehousing Specialists · importance 3.6 · direct LLM exposure
• Evaluate project plans and proposals to assess feasibility issues. · Computer and Information Research Scientists · importance 3.5 · exposure with tools

Occupations that perform this

• Statisticians
• Telecommunications Engineering Specialists
• Computer and Information Systems Managers
• Data Warehousing Specialists
• Computer and Information Research Scientists

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-evaluate-project-designs-to-determine-adequacy-or-feasibility,
  title  = {Evaluate project designs to determine adequacy or feasibility.},
  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/evaluate-project-designs-to-determine-adequacy-or-feasibility}
}