As of August 2026, Supply Chain Managers has an AI-exposure score of 60/100 (Elevated 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.

AI Exposure Score for

Supply Chain Managers

60/100
Elevated exposure
LowModerateElevatedHighVery High

More exposed than 64% of the roles we track. Median pay ~US$107,230. About 18,500 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 Supply Chain Managers?

No exposure score can predict whether AI will replace this role. The 60/100 score means our current model estimates elevated 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 Elevated 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.

Data sources, not endorsements: O*NET and curated role data; empirical AI signals where matched; BLS employment, pay, and demand as separate context.Methodology Data sources
Role snapshot

What this role usually involves

O*NET 29.1 exact occupation

Direct or coordinate production, purchasing, warehousing, distribution, or financial forecasting services or activities to limit costs and improve accuracy, customer service, or safety. Examine existing procedures or opportunities for streamlining activities to meet product distribution needs. Direct the movement, storage, or processing of inventory.

Common titles
Global Supply Chain DirectorMaterial Requirements Planning ManagerSupply Chain DirectorSupply Chain ManagerSolution Design and Analysis Manager
O*NET job-zone preparation
Job Zone 4 · Considerable Preparation Needed Most of these occupations require a four-year bachelor's degree, but some do not. A considerable amount of work-related skill, knowledge, or experience is needed for these occupations.

Broad guidance for this preparation level; exact requirements vary by role and employer.

Skills and knowledge
CoordinationJudgment and Decision MakingMonitoringReading ComprehensionSpeakingTime Management
Work context
Frequent contact with othersIndoor controlled settingDecision latitude

Source: O*NET 29.1 exact occupation - Supply Chain Managers, SOC 11-3071.04. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.

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Supply Chain Managers tasks, by AI exposure

Automatable

No automatable tasks identified for this role - its individually-assessed tasks split 75% augmentable / 25% durable.

Augmentable
  • Analyze information about supplier performance or procurement program success.
  • Document physical supply chain processes, such as workflows, cycle times, position responsibilities, or system flows.
13 more augmentable tasks locked in the report.
Durable
  • Negotiate prices and terms with suppliers, vendors, or freight forwarders.
  • Identify or qualify new suppliers in collaboration with other departments, such as procurement, engineering, or quality assurance.
3 more durable tasks locked in the report.

We analyzed all 20 Supply Chain Managers tasks - 15 augmentable and 5 durable. The full task map - every task with exactly what to do about each - is in your Career Report.

Your report unlocks three concrete artifacts

Full task map

Every task scored with what to automate, augment, or protect.

Adjacent path comparison

Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.

30/60/90 plan + PDF

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

No evidence-backed lower-exposure match appears in this O*NET adjacency set. The adjacent paths below remain useful comparisons; the strongest resilience moves are task-level.

Transportation, Storage, and Distribution Managers
64% skills overlap; 2 points higher - similar exposure within the 5-point model resolution; Elevated band; ~US$107,230
View path
62
7 more adjacent paths with exposure deltas, salary, demand, and reachability in your Career Report.
Agent Reality Check (on-site workflow preview)

Analyze information about supplier performance or procurement program success.

Check what deployed AI agents can attempt on tasks like this using dated capability evidence. You review the real task before any analysis runs.
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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.

Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026

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Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.

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Supply Chain Managers - median pay by US state (BLS OEWS, USD)

New York: US$127,180California: US$123,780Florida: US$101,570Texas: US$100,700

Median annual wage, in USD. US national: US$107,230. More states are being added.

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