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AI Automation Index
Will AI Replace Supply Chain Managers?
Task-level automation exposure for Supply Chain Managers: 30 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
56%
weighted task index
30 of 30 tasks scored
Median Salary
$107,230 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
221,180 people hold this job — size, not growth
Projected 2025–35
+6.1%
employment change
18,300 openings a year · BLS line item
Pay by state
BLS OEWS publishes 54 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$56,390 – $145,000
Highest medians
Delaware $145,000
Washington $136,500
Colorado $132,610
District of Columbia $132,180
New Jersey $130,610
Lowest medians
Virgin Islands $56,390
Guam $83,360
Puerto Rico $83,560
Mississippi $85,770
Arkansas $89,200
State figures come from the 11-3071 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 56%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 58%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 6%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 5/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
30 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 44%
13 tasks
Medium exposure (≥ 35%) 52%
16 tasks
Low exposure (below 35%) 4%
1 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#20942 · Core · 63% automatable
Determine appropriate equipment and staffing levels to load, unload, move, or store materials.
data analysis — Cost/material estimates from data; human verifies
Estimate labor requirements. Estimate cost or material requirements.
#20943 · Core · 68% automatable
Manage activities related to strategic or tactical purchasing, material requirements planning, controlling inventory, warehousing, or receiving.
data analysis — Inventory management systems; human handles physical counts
Manage inventories of products or organizational resources.
#15680 · Core · 30% automatable
Select transportation routes to maximize economy by combining shipments or consolidating warehousing and distribution.
decision support — Transportation changes need operational authority and execution
Implement transportation changes to reduce environmental impact.
#15695 · Core · 62% automatable
Define performance metrics for measurement, comparison, or evaluation of supply chain factors, such as product cost or quality.
text generation — AI drafts evaluation procedures; human adapts to org
Develop organizational goals or objectives. Develop procedures to evaluate organizational activities.
#20944 · Core · 45% automatable
Implement new or improved supply chain processes to improve efficiency or performance.
decision support — AI plans projects; human owns execution and stakeholders
Manage operations, research, or logistics projects.
#15700 · Core · 58% automatable
Develop procedures for coordination of supply chain management with other functional areas, such as sales, marketing, finance, production, or quality assurance.
decision support — AI drafts strategies; human owns operational judgment
Develop operating strategies, plans, or procedures.
#15694 · Core · 45% automatable
Confer with supply chain planners to forecast demand or create supply plans that ensure availability of materials or products.
interpersonal — Coordinating work through live human interaction
Confer with organizational members to accomplish work activities.
#15696 · Core · 72% automatable
Analyze inventories to determine how to increase inventory turns, reduce waste, or optimize customer service.
data analysis — Operational data analysis; manager owns decisions
Analyze data to inform operational decisions or activities.
#15685 · Core · 35% automatable
Negotiate prices and terms with suppliers, vendors, or freight forwarders.
interpersonal — Logistics contract negotiation needs mandate
Negotiate contracts for transportation, distribution, or logistics services.
#15697 · Core · 72% automatable
Analyze information about supplier performance or procurement program success.
data analysis — Effectiveness assessment from data; human reviews
Analyze data to assess operational or project effectiveness.
#20945 · Core · 55% automatable
Monitor suppliers' activities to assess performance in meeting quality or delivery requirements.
data analysis — AI analyzes performance metrics; human judges people context
Monitor performance of organizational members or partners.
#15701 · Core · 47% automatable
Design or implement supply chains that support business strategies adapted to changing market conditions, new business opportunities, or cost reduction strategies.
decision support — AI proposes procedures; human validates fit
Implement organizational process or policy changes. Develop organizational methods or procedures.
#15688 · Core · 60% automatable
Meet with suppliers to discuss performance metrics, to provide performance feedback, or to discuss production forecasts or changes.
text generation — Information exchange coordination largely automatable
Coordinate with external parties to exchange information.
#20946 · Core · 78% automatable
Monitor forecasts and quotas to identify changes and predict effects on supply chain activities.
information retrieval — AI monitors news and events affecting operations
Monitor external affairs or events affecting business operations.
#15698 · Core · 45% automatable
Participate in the coordination of engineering changes, product line extensions, or new product launches to ensure orderly and timely transitions in material or production flow.
decision support — AI plans projects; human owns execution and stakeholders
Manage operations, research, or logistics projects.
#20947 · Core · 45% automatable
Identify or qualify new suppliers in collaboration with other departments, such as procurement, engineering, or quality assurance.
interpersonal — Coordinating work through live human interaction
Confer with organizational members to accomplish work activities.
#15693 · Core · 47% automatable
Design or implement plant warehousing strategies for production materials or finished products.
decision support — AI drafts strategies; human owns operational judgment
Implement organizational process or policy changes. Develop operating strategies, plans, or procedures.
#19541 · Core · 47% automatable
Design, implement, or oversee product take back or reverse logistics programs to ensure products are recycled, reused, or responsibly disposed.
text generation — Policy drafting aided; governance decisions human
Implement organizational process or policy changes. Develop sustainable organizational policies or practices.
#15692 · Core · 50% automatable
Develop or implement procedures or systems to evaluate or select suppliers.
text generation — AI drafts evaluation procedures; human adapts to org
Implement organizational process or policy changes. Develop procedures to evaluate organizational activities.
#15691 · Core · 75% automatable
Document physical supply chain processes, such as workflows, cycle times, position responsibilities, or system flows.
text generation — Document organizational procedures from provided content
Document organizational or operational procedures.
#15681 · Core · 75% automatable
Diagram supply chain models to help facilitate discussions with customers.
text generation — Document organizational procedures from provided content
Document organizational or operational procedures.
#19542 · Core · 52% automatable
Evaluate and select information or other technology solutions to improve tracking and reporting of materials or products distribution, storage, or inventory.
text generation — Policy drafting aided; governance decisions human
Evaluate quality of materials or products. Develop sustainable organizational policies or practices.
#19543 · Core · 72% automatable
Identify opportunities to reuse or recycle materials to minimize consumption of new materials, minimize waste, or to convert wastes to by-products.
decision support — AI surfaces green initiative ideas; human validates
Identify opportunities for green initiatives.
#19546 · Core · 35% automatable
Review or update supply chain practices in accordance with new or changing environmental policies, standards, regulations, or laws.
interpersonal — Policy implementation requires organizational authority and change management
Implement organizational process or policy changes.
#19540 · Core · 47% automatable
Design or implement supply chains that support environmental policies.
text generation — Policy drafting aided; governance decisions human
Implement organizational process or policy changes. Develop sustainable organizational policies or practices.
#20948 · Supplemental · 65% automatable
Forecast material costs or develop standard cost lists.
data analysis — Cost/material estimates from data; human verifies
Estimate cost or material requirements.
#19545 · Supplemental · 72% automatable
Locate or select biodegradable, non-toxic, or other environmentally friendly raw materials for manufacturing processes.
decision support — AI surfaces green initiative ideas; human validates
Identify opportunities for green initiatives.
#20949 · Supplemental · 65% automatable
Appraise vendor manufacturing capabilities through on-site observations or other measurements.
decision support — Potential assessment aided by research, human decides
Evaluate potential of products, technologies, or resources.
#19539 · Supplemental · 55% automatable
Conduct or oversee the conduct of life cycle analyses to determine the environmental impacts of products, processes, or systems.
data analysis — Evaluation aided; regulatory judgment and site data human
Evaluate environmental impact of operational or development activities.
#19544 · Supplemental · 55% automatable
Investigate or review the carbon footprints and environmental performance records of current or potential storage and distribution service providers.
data analysis — Evaluation aided; regulatory judgment and site data human
Evaluate environmental impact of operational or development activities.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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