As of August 2026,
Compensation and Benefits Managers has an AI-exposure score of 70/100
(High exposure) on the AI-Safe Careers index. This is an estimate of task
exposure, not a prediction of job loss.
Score inputs for this role:
This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Anthropic Economic Index (June 26, 2026), Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.
Compensation and Benefits Managers
More exposed than 90% of the roles we track. Median pay ~US$149,230. About 1,500 projected openings a year (BLS 2024–34 - growth plus replacement).
Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.
Will AI replace Compensation and Benefits Managers?
No exposure score can predict whether AI will replace this role. The 70/100 score means our current model estimates high task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.
Early-career context (study ages 22-25)
This role is in the High exposure band, but its assessed task mix is not automation-heavy. The study found the decline concentrated where AI was more likely to automate rather than augment work, so the headline figure should not be applied directly.
The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.
Use the task map to identify durable work and the skills worth building early.
Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision
This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.
How this role compares to similar Management roles
What this role usually involves
Plan, direct, or coordinate compensation and benefits activities of an organization.
Broad guidance for this preparation level; exact requirements vary by role and employer.
Source: O*NET 29.1 exact occupation - Compensation and Benefits Managers, SOC 11-3111.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.
Compensation and Benefits Managers tasks, by AI exposure
- Maintain records and compile statistical reports concerning personnel-related data, such as hires, transfers, performance appraisals, and absenteeism rates.
- Direct preparation and distribution of written and verbal information to inform employees of benefits, compensation, and personnel policies.
- Prepare detailed job descriptions and classification systems and define job levels and families, in partnership with other managers.
- Mediate between benefits providers and employees, such as by assisting in handling employees' benefits-related questions or taking suggestions.
- Identify and implement benefits to increase the quality of life for employees by working with brokers and researching benefits issues.
No durable tasks identified for this role - its individually-assessed tasks split 85% augmentable / 15% automatable.
We analyzed all 20 Compensation and Benefits Managers tasks - 3 automatable and 17 augmentable. The full task map - every task with exactly what to do about each - is in your Career Report.
Your report unlocks three concrete artifacts
Every task scored with what to automate, augment, or protect.
Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.
A keepable roadmap plus resume and LinkedIn repositioning.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.
Adjacent career paths
Relatedness shows how reachable a move may be. A path is labeled lower exposure only when its score is at least 6 points lower; every row shows the measured difference.
Maintain records and compile statistical reports concerning personnel-related data, such as hires, transfers, performance appraisals, and absenteeism rates.
Your AI-Safe Career Report
Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.
AI was the most-cited reason for U.S. layoffs through mid-2026 - the workers who adapt earliest fare best. - Challenger, Gray & Christmas, 2026The upside: Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026
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Compensation and Benefits Managers - median pay by US state (BLS OEWS, USD)
Median annual wage, in USD. US national: US$149,230. More states are being added.