Technology · SOC 15-2031
AI excels at running optimization models, but framing the right problem and translating results into organizational decisions stays human.
A large share of tasks is exposed; the role will change a lot.
Timeline: AI optimization engines are automating standard OR models for logistics and scheduling today; within 4-6 years, OR analysts shift toward problem design, model governance, and translating AI outputs into executive decisions.
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$132,000 median pay
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AI job-risk card
Operations Research Analysts is at risk on AIFear. A large share of tasks is exposed; the role will change a lot.
AIFear.com
Our AI Fear Score for Operations Research Analysts is 58/100 (At risk). A large share of tasks is exposed; the role will change a lot.
58 out of 100, based on an AI-model review of this occupation's O*NET tasks against what current AI can actually do.
Most exposed: Presenting mathematical modeling results in standard report formats, Validating data inputs and running statistical tests on collected data, Preparing management reports with templated structure, Running computational models across specified scenario sets. Harder to automate: Observing real operations to surface problems models miss, Reformulating models when initial assumptions prove wrong, Decomposing complex systems into mathematical components, Persuading management to act on counterintuitive findings.
Lean into AI-assisted optimization and simulation, Machine learning for decision support, Business communication and visualization, Supply chain and logistics analytics, Experimental design. Consider roles such as Decision Science Manager or Supply Chain Analytics Lead or Management Consulting Analyst.
Tasks, skills and AI-exposure for this role were reviewed by an AI model against its O*NET task profile (curated roles use published research anchors). Pay and employment, where shown, are U.S. BLS OEWS (May 2024) figures. This is an estimate, not a prediction about any individual's job. Compare all occupations.