Operations Research Analysts: daily tasks & AI impact
This page breaks Operations Research Analysts into the top 15 daily O*NET tasks and scores each for Generative AI automation probability. Those task scores roll up to an overall vulnerability index of 57/100 (Moderate automation risk). Struck-through rows are ≥80% automatable; highlighted safer rows are under 30% or primarily physical.
High-automation exposure
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Durable human work
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.
| Task | Importance | AI probability | Nature |
|---|---|---|---|
| Present the results of mathematical modeling and data analysis to management or other end users. Core | 4.62 | — | — |
| Define data requirements, and gather and validate information, applying judgment and statistical tests. Core | 4.55 | — | — |
| Perform validation and testing of models to ensure adequacy, and reformulate models, as necessary. Core | 4.52 | — | — |
| Prepare management reports defining and evaluating problems and recommending solutions. Core | 4.5 | — | — |
| Collaborate with others in the organization to ensure successful implementation of chosen problem solutions. Core | 4.43 | — | — |
| Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters. Core | 4.38 | — | — |
| Observe the current system in operation, and gather and analyze information about each of the component problems, using a variety of sources. Core | 4.38 | — | — |
| Analyze information obtained from management to conceptualize and define operational problems. Core | 4.33 | — | — |
| Study and analyze information about alternative courses of action to determine which plan will offer the best outcomes. Core | 4.29 | — | — |
| Collaborate with senior managers and decision makers to identify and solve a variety of problems and to clarify management objectives. Core | 4.25 | — | — |
| Specify manipulative or computational methods to be applied to models. Core | 4.05 | — | — |
| Design, conduct, and evaluate experimental operational models in cases where models cannot be developed from existing data. Core | 3.95 | — | — |
| Develop and apply time and cost networks to plan, control, and review large projects. Core | 3.78 | — | — |
| Break systems into their components, assign numerical values to each component, and examine the mathematical relationships between them. Core | 3.7 | — | — |
| Educate staff in the use of mathematical models. Core | 3.65 | — | — |
What remains human
No tasks currently fall under the safe threshold for this occupation.
FAQ
Which Operations Research Analysts tasks are most exposed to AI?
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Which Operations Research Analysts tasks are safest from Generative AI?
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
How should I read the Operations Research Analysts task table?
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.