Analyze data to identify trends or relationships among variables.

Analyze data to identify trends or relationships among variables. is a detailed work activity in O*NET — a concrete unit of work shared across 16 occupations and seen in 27 occupation-specific tasks. It rolls up into the broader work activity Analyze scientific or applied data using mathematical principles. in Analyzing Data or Information .

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 27 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 26 (96%) 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 14 of these tasks, with a mean mapped-usage share of 0.097% 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.

• Assess the identity, strength, or purity of medications. · Pharmacists · importance 4.7 · no direct exposure
• Analyze and interpret statistical data to identify significant differences in relationships among sources of information. · Statisticians · importance 4.7 · exposure with tools
• Draw conclusions or make predictions, based on data summaries or statistical analyses. · Biostatisticians · importance 4.5 · exposure with tools
• Analyze prescribing trends to monitor patient compliance and to prevent excessive usage or harmful interactions. · Pharmacists · importance 4.4 · exposure with tools
• Identify relationships and trends in data, as well as any factors that could affect the results of research. · Statisticians · importance 4.3 · exposure with tools
• Identify groups at risk for specific preventable diseases or injuries. · Preventive Medicine Physicians · importance 4.2 · exposure with tools
• Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information. · Actuaries · importance 4.2 · exposure with tools
• Develop or implement data analysis algorithms. · Biostatisticians · importance 4.2 · direct LLM exposure
• Prepare statistical data for inclusion in reports to data monitoring committees, federal regulatory agencies, managers, or clients. · Biostatisticians · importance 4.2 · exposure with tools
• Program and use computers to store, process, and analyze data. · Biologists · importance 4.1 · direct LLM exposure
• Reconstruct crime scenes to determine relationships among pieces of evidence. · Forensic Science Technicians · importance 4.1 · exposure with tools
• Assemble sets of assumptions, and explore the consequences of each set. · Mathematicians · importance 4.0 · direct LLM exposure
• Perform integrated or computerized Geographic Information Systems (GIS) analyses to address scientific problems. · Geographic Information Systems Technologists and Technicians · importance 4.0 · exposure with tools
• Prepare project status reports by collecting, analyzing, and summarizing information and trends. · Information Technology Project Managers · importance 4.0 · exposure with tools
• Perform computations and apply methods of numerical analysis to data. · Mathematicians · importance 3.9 · direct LLM exposure
• Interpret aerial or ortho photographs. · Geographic Information Systems Technologists and Technicians · importance 3.9 · exposure with tools
• Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols. · Mathematicians · importance 3.9 · direct LLM exposure
• Analyze information from traffic counting programs. · Transportation Planners · importance 3.9 · exposure with tools
• Identify and evaluate industry trends in database systems to serve as a source of information and advice for upper management. · Database Architects · importance 3.9 · exposure with tools
• Perform system analysis, data analysis or programming, using a variety of computer languages and procedures. · Data Warehousing Specialists · importance 3.8 · direct LLM exposure
• Create, analyze, report, convert, or transfer data, using specialized applications program software. · Geographic Information Systems Technologists and Technicians · importance 3.7 · exposure with tools
• Break systems into their components, assign numerical values to each component, and examine the mathematical relationships between them. · Operations Research Analysts · importance 3.7 · direct LLM exposure
• Analyze incident data to identify trends in injuries, illnesses, accidents, or other hazards. · Occupational Health and Safety Specialists · importance 3.6 · exposure with tools
• Conduct logical analyses of business, scientific, engineering, and other technical problems, formulating mathematical models of problems for solution by computers. · Computer and Information Research Scientists · importance 3.6 · direct LLM exposure
• Conduct historical analyses of test results. · Software Quality Assurance Analysts and Testers · importance 3.3 · direct LLM exposure
• Identify and evaluate industry trends in database systems to serve as a source of information and advice for upper management. · Database Administrators · importance 2.8 · exposure with tools
• Identify relationships and trends or any factors that could affect the results of research. · Data Scientists · exposure with tools

Occupations that perform this

• Pharmacists
• Statisticians
• Preventive Medicine Physicians
• Actuaries
• Biologists
• Forensic Science Technicians
• Geographic Information Systems Technologists and Technicians
• Mathematicians
• Database Architects
• Transportation Planners
• Operations Research Analysts
• Occupational Health and Safety Specialists
• Computer and Information Research Scientists
• Software Quality Assurance Analysts and Testers
• Database Administrators
• Data 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-analyze-data-to-identify-trends-or-relationships-among-variables,
  title  = {Analyze data to identify trends or relationships among variables.},
  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/analyze-data-to-identify-trends-or-relationships-among-variables}
}