BETA
Updated: May 6
BETA
Updated: May 6
CLOSE
The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
Navigate your career with your free AI Career Coach. Research-backed, designed with career experts.
The AI Resilience Report is a project from CareerVillage®, a registered 501(c)(3) nonprofit.
Mostly Resilient
Last Update: 4/23/2026
Your role’s AI Resilience Score is
53.6%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Low
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
High
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
This result is backed by strong agreement across multiple data sources.
Contributing sources
AI Resilience Report forOperations Research Analysts
Operations Research Analysts are somewhat more resilient to AI impacts than most occupations, according to our analysis of 7 sources.
A career as an Operations Research Analyst is considered "Mostly Resilient" because while AI can handle many technical tasks like building and solving models, the job still heavily relies on human skills. Analysts need to break down complex systems, communicate with managers, and collaborate on strategic decisions, which require judgment, experience, and teamwork—areas where AI falls short.
Read full analysisLearn more about how you can thrive in this position
View analysis
Chat with Coach
Latest news
More career infoAnalysisChatNewsMoreLearn more about how you can thrive in this position
View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreThis role is mostly resilient
A career as an Operations Research Analyst is considered "Mostly Resilient" because while AI can handle many technical tasks like building and solving models, the job still heavily relies on human skills. Analysts need to break down complex systems, communicate with managers, and collaborate on strategic decisions, which require judgment, experience, and teamwork—areas where AI falls short.
Read full analysisAnalysis of Current AI Resilience
Operations Research Anlys
Updated Quarterly • Last Update: 2/17/2026
How is AI changing Operations Research Anlys jobs?
Operations research analysts use a lot of math and computer models, and AI is starting to help with some of that work. For example, researchers have shown that machine learning can even pick the best solver (optimization algorithm) for a scheduling problem automatically [1]. Industry sources note that AI tools can update optimization models in real time — for instance, as goods move through a supply chain — making recommendations faster [2].
An operations-research society article also explains that AI can crunch huge data sets to build more accurate predictive models (for demand forecasting, routing, etc.) than older methods [3]. In other words, many of the technical tasks (like building or solving models) are being augmented by smarter software.
However, the human side of the job is still strong. The official job description lists duties like “conceptualiz\[ing\] and defin\[ing\] operational problems” and works with senior managers or teams to implement solutions [4]. These tasks – breaking a system into parts, talking with managers, and collaborating on strategy – rely on judgment, experience, and communication.
AI doesn’t understand context or goals the way people do. So far, those parts of the job remain mostly manual, with analysts using their human skills to interpret results and make decisions.
Sources
How fast is AI adoption growing for Operations Research Anlys?
AI tools for operations research are definitely available, but adoption is gradual. Powerful optimization software already exists – for instance, IBM’s ILOG CPLEX and Google’s open-source OR-Tools are industry-standard solvers shown to work very well on complex problems [1]. In theory, using these tools or new AI could save companies time and money. (By one estimate, supply-chain systems combining AI forecasts with optimization cuts costs and late shipments [2].) Also, many OR analysts earn high salaries (around $82,000 median per year [5]), so there is financial incentive to automate routine parts of their work.
On the other hand, implementing AI is not cheap or simple. Firms must invest in data infrastructure and new software. Because OR work often affects important outcomes (like logistics, production, or policy), companies tend to keep people in the loop.
Experts note the importance of “strik\[ing\] the right balance between autonomous decision-making and human oversight” [3]. In short, AI will likely augment more than replace OR analysts for now: businesses may use AI tools where they clearly cut costs or boost speed, but they still count on human analysts for interpretation, creativity, and teamwork.
Sources
Help us improve this report.
Tell us if this analysis feels accurate or we missed something.
Share your feedback
More Career Info
Career: Operations Research Analysts
They solve problems for businesses by using math and computers to find the best ways to save time, money, and resources.
Parent Careers
Employment & Wage Data
Median Wage
$91,290
Jobs (2024)
112,100
Growth (2024-34)
+21.5%
Annual Openings
9,600
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Collaborate with others in the organization to ensure successful implementation of chosen problem solutions.
2
Define data requirements and gather and validate information, applying judgment and statistical tests.
3
Collaborate with senior managers and decision makers to identify and solve a variety of problems and to clarify management objectives.
4
Analyze information obtained from management to conceptualize and define operational problems.
5
Develop and apply time and cost networks to plan, control, and review large projects.
6
Design, conduct, and evaluate experimental operational models in cases where models cannot be developed from existing data.
7
Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
© 2026 CareerVillage.org. All rights reserved.
The AI Resilience Report is a project from CareerVillage.org®, a registered 501(c)(3) nonprofit.
Built with ❤️ by Sandbox Web
The AI Resilience Report is governed by CareerVillage.org’s Privacy Policy and Terms of Service. This site is not affiliated with Anthropic, Microsoft, or any other data provider and doesn't necessarily represent their viewpoints. This site is being actively updated, and may sometimes contain errors or require improvement in wording or data. To report an error or request a change, please contact air@careervillage.org.