Will AI replace Operations Research Analysts?
On paper, AI could touch ~63% of the work in Operations Research Analysts — and unlike most jobs, it's already showing up in the real workday, not just the theory.
O*NET-SOC 15-2031
How your 15 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a high share of this job's tasks (~63%). By late 2025, real-world AI use had reached about 43% of its task activity (already common). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
Read this as a range, not a verdict
The signals here partly disagree — AI's theoretical reach (~63%) and its real-world use (~43%) tell different stories. AI-risk scores also shift a lot by which model does the rating (2.7%–51.5% in one 2026 study), so this is a direction of travel, not a fixed answer.
See all 15 tasks, ratedBased on real task-level AI scores — click to collapse
- Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.
- Break systems into their components, assign numerical values to each component, and examine the mathematical relationships between them.
- Design, conduct, and evaluate experimental operational models in cases where models cannot be developed from existing data.
- Specify manipulative or computational methods to be applied to models.
- Perform validation and testing of models to ensure adequacy, and reformulate models, as necessary.
- Collaborate with senior managers and decision makers to identify and solve a variety of problems and to clarify management objectives.
- Present the results of mathematical modeling and data analysis to management or other end users.
- Collaborate with others in the organization to ensure successful implementation of chosen problem solutions.
- Analyze information obtained from management to conceptualize and define operational problems.
- Study and analyze information about alternative courses of action to determine which plan will offer the best outcomes.
- Prepare management reports defining and evaluating problems and recommending solutions.
- Define data requirements, and gather and validate information, applying judgment and statistical tests.
- Observe the current system in operation, and gather and analyze information about each of the component problems, using a variety of sources.
- Educate staff in the use of mathematical models.
- Develop and apply time and cost networks to plan, control, and review large projects.
- ⚠️ None — every core task is at least partly within AI's reach. The job won't vanish, but almost all of it changes.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.