Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.

“Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.” is a core task performed by Operations Research Analysts. Among the occupation's 16 rated tasks, workers place it 11th by importance (#6 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.

• Develop scientific or mathematical theories or models. in Thinking Creatively

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: T2.

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
• 17% of that use is work-related
• Most common interaction: directive
• Average autonomy of the AI: 3.6 (1–5; higher = more autonomous)
• 82% 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

• Present the results of mathematical modeling and data analysis to management or other end users. · importance 4.6
• Define data requirements, and gather and validate information, applying judgment and statistical tests. · importance 4.5
• Perform validation and testing of models to ensure adequacy, and reformulate models, as necessary. · importance 4.5
• Prepare management reports defining and evaluating problems and recommending solutions. · importance 4.5
• Collaborate with others in the organization to ensure successful implementation of chosen problem solutions. · importance 4.4
• Observe the current system in operation, and gather and analyze information about each of the component problems, using a variety of sources. · importance 4.4
• Analyze information obtained from management to conceptualize and define operational problems. · importance 4.3
• Study and analyze information about alternative courses of action to determine which plan will offer the best outcomes. · importance 4.3
• Collaborate with senior managers and decision makers to identify and solve a variety of problems and to clarify management objectives. · importance 4.3
• Specify manipulative or computational methods to be applied to models. · importance 4.0
• Design, conduct, and evaluate experimental operational models in cases where models cannot be developed from existing data. · importance 4.0
• Develop and apply time and cost networks to plan, control, and review large projects. · importance 3.8
• Break systems into their components, assign numerical values to each component, and examine the mathematical relationships between them. · importance 3.7
• Educate staff in the use of mathematical models. · importance 3.6

See all tasks on the Operations Research Analysts 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-7377,
  title  = {Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.},
  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-7377}
}