Create, populate, or maintain databases for tracking validation activities, test results, or validated systems.

“Create, populate, or maintain databases for tracking validation activities, test results, or validated systems.” is a core task performed by Validation Engineers. Among the occupation's 22 rated tasks, workers place it 11th by importance (#12 most important). About 100% of workers say it is relevant to their job.

This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.

Work activities this task rolls up to

O*NET groups concrete tasks into broader work activities shared across many occupations.

• Operate computer systems or computerized equipment. in Working with Computers

AI exposure

The OpenAI / Eloundou “GPTs are GPTs” study rates this task E1. Direct exposure — a language model could plausibly cut the time to do this task by at least half.

Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 1.00. Automation potential label: T3.

How AI is actually used on this kind of task

The Anthropic Economic Index observes how people actually use AI on tasks like this one across millions of real conversations.

• 0.019% share of AI-use records mapped to this task
• 57% of that use is work-related
• Most common interaction: directive
• Average autonomy of the AI: 3.4 (1–5; higher = more autonomous)
• 87% of interactions still needed a human in the loop

Observed AI use describes people choosing to use AI as a tool on this kind of task today. It is augmentation and assistance, not a measure of jobs replaced.

Working with AI vs. handing it off

Of the AI conversations mapped to this task, the split between people working alongside AI and people delegating the task to it.

How people interact with AI on this task

Other tasks in this occupation

• Study product characteristics or customer requirements to determine validation objectives and standards. · importance 4.6
• Analyze validation test data to determine whether systems or processes have met validation criteria or to identify root causes of production problems. · importance 4.5
• Develop validation master plans, process flow diagrams, test cases, or standard operating procedures. · importance 4.4
• Prepare detailed reports or design statements, based on results of validation and qualification tests or reviews of procedures and protocols. · importance 4.3
• Maintain validation test equipment. · importance 4.2
• Conduct validation or qualification tests of new or existing processes, equipment, or software in accordance with internal protocols or external standards. · importance 4.2
• Communicate with regulatory agencies regarding compliance documentation or validation results. · importance 4.1
• Prepare, maintain, or review validation and compliance documentation, such as engineering change notices, schematics, or protocols. · importance 4.1
• Recommend resolution of identified deviations from established product or process standards. · importance 4.0
• Design validation study features, such as sampling, testing, or analytical methodologies. · importance 3.9
• Prepare validation or performance qualification protocols for new or modified manufacturing processes, systems, or equipment for production of pharmaceuticals, electronics, or other products. · importance 3.8
• Resolve testing problems by modifying testing methods or revising test objectives and standards. · importance 3.8
• Conduct audits of validation or performance qualification processes to ensure compliance with internal or regulatory requirements. · importance 3.7
• Draw samples of raw materials, intermediate products, or finished products for validation testing. · importance 3.6

See all tasks on the Validation Engineers page.

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-task-18133,
  title  = {Create, populate, or maintain databases for tracking validation activities, test results, or validated systems.},
  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/tasks/task-18133}
}