Computer and Mathematical · United States (national)
Operations Research Analysts
How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is moderately exposed to automation, and a near-term shift looks unlikely.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 50.9 to 74.9
Physical / roboticsrange 0.0 to 21.2
When the change is likely
Largely unaffectedlocal demand growing
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Stay sharp; urgency is low
This role looks durable. Keep your skills current and watch for shifts in your field.
2
Lean into the human edge
The exposed parts are routine and cognitive. Invest in judgment, client relationships, and complex problem-solving that AI still cannot do.
3
Pivot toward Software Developers
It is skill-adjacent and less exposed (44.7 vs 63). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
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Which of my tasks are exposed
Present the results of mathematical modeling and data analysis to management or other end users.
50.0
Define data requirements, and gather and validate information, applying judgment and statistical tests.
50.0
Perform validation and testing of models to ensure adequacy, and reformulate models, as necessary.
50.0
Prepare management reports defining and evaluating problems and recommending solutions.
50.0
Collaborate with others in the organization to ensure successful implementation of chosen problem solutions.
100.0
Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.
62.9
Observe the current system in operation, and gather and analyze information about each of the component problems, using a variety of sources.
50.0
Analyze information obtained from management to conceptualize and define operational problems.
50.0
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Collaborate with others in the organization to ensure successful implementation of chosen problem solutions.
Task: Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.
Local demand is growing
Lower-risk adjacent roles
Software Developers
44.7
Computer Systems Analysts
47.1
Management Analysts
50.0
Computer and Information Research Scientists
50.0
Business Intelligence Analysts
57.6
Data Scientists
59.4
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map Operations Research Analysts to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 62.9, robotics 9.2.
The timeline comes from the higher axis (62.9), shifted for local demand (growing), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.