Share and intensity of work current AI systems can materially affect.
SOC 51-1011
First-Line Supervisors of Production Workers AI displacement risk
Production supervisors set work schedules, inspect output, enforce safety rules, and coordinate between departments. Manufacturing execution systems now track output in real time, but supervisors run the shift: reallocating people when machines go down, enforcing safety, and answering for the numbers.
Likely potential for exposed tasks to move to software after workflow integration.
As production automation raises output per worker, the supervisor's job shifts toward exception management — handling what the line cannot. This is the advancement path for assemblers and operators across the production cluster.
Distribution
Where First-Line Supervisors of Production Workers sits across 620 tracked roles
Displacement pressure 24 — higher than 32% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
20 O*NET task statements matched to SOC 51-1011. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $74,450 (May 2025, US national). The latest BLS row matched SOC 51-1011.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify First-Line Supervisors of Production Workers
SOC 51-1011 places this role in the paper's all-other occupation group. These group-level outcomes do not change the 24/100 role score and are not an occupation forecast.
+1.1% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +1.6% GDP and 3.9% unemployment.
+5.9% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +8.3% GDP and 4.6% unemployment.
+33.6% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for First-Line Supervisors of Production Workers
The current evidence import matched 20 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks20
SOC51-1011
- Core task / ID 8450
Enforce safety and sanitation regulations.
- Core task / ID 20155
Keep records of employees' attendance and hours worked.
- Core task / ID 8455
Inspect materials, products, or equipment to detect defects or malfunctions.
- Core task / ID 8452
Read and analyze charts, work orders, production schedules, and other records and reports to determine production requirements and to evaluate current production estimates and outputs.
- Core task / ID 8454
Plan and establish work schedules, assignments, and production sequences to meet production goals.
- Core task / ID 8453
Confer with other supervisors to coordinate operations and activities within or between departments.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Plan work schedules and production sequences
Exposure 48, automation 25%, augmentation 56%.
O*NET evidence: Plan and establish work schedules, assignments, and production sequences to meet produc... (ID 8454)
Inspect materials and products to detect defects
Exposure 34, automation 16%, augmentation 50%.
O*NET evidence: Inspect materials, products, or equipment to detect defects or malfunctions. (ID 8455)
Enforce safety and sanitation regulations
Exposure 30, automation 13%, augmentation 50%.
O*NET evidence: Enforce safety and sanitation regulations. (ID 8450)
Confer with other supervisors to coordinate operations
Exposure 26, automation 10%, augmentation 50%.
O*NET evidence: Confer with other supervisors to coordinate operations and activities within or between... (ID 8453)
TaskExposureAutomationAugmentation
Plan work schedules and production sequences4825%56%
Inspect materials and products to detect defects3416%50%
Enforce safety and sanitation regulations3013%50%
Confer with other supervisors to coordinate operations2610%50%
Transition pathways
Adjacent moves that preserve existing skills
credentialed transition
LowPlant Manager
Training horizon: 12-24 months. Skill overlap 66. Wage preservation signal 140.
- Own plant P&L
- Lead continuous improvement
- Manage multi-shift operations
role redesign
LowManufacturing Operations Analyst
Training horizon: 3-6 months. Skill overlap 60. Wage preservation signal 112.
- Analyze line data
- Model labor and throughput
- Support automation projects
Comparison guides
Compare the next move before you commit
12-24 months
First-Line Supervisors of Production Workers to Plant Manager
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from First-Line Supervisors of Production Workers into Plant Manager.
3-6 months
First-Line Supervisors of Production Workers to Manufacturing Operations Analyst
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from First-Line Supervisors of Production Workers into Manufacturing Operations Analyst.
What the AI risk score means for First-Line Supervisors of Production Workers
The displacement pressure score for First-Line Supervisors of Production Workers is 24. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Plan work schedules and production sequences carries 25% automation pressure, while Plan work schedules and production sequences carries 56% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $74,450 (May 2025, US national). Employment context: The near-move target for the production floor. Typical education: Production experience plus supervisory training.
Wage vulnerability is 34, while transition feasibility is 68. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Low displacement pressure
- MES tracks output, supervisors run shifts
- Exception management grows
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For First-Line Supervisors of Production Workers, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Production scheduling
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Quality inspection
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Safety enforcement
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Shift coordination
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Plant Manager, such as own plant p&l.
- By 90 days, compare internal openings and external postings for Plant Manager or Manufacturing Operations Analyst and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and First-Line Supervisors of Production Workers
Will AI replace First-Line Supervisors of Production Workers?
Production supervisors set work schedules, inspect output, enforce safety rules, and coordinate between departments. Manufacturing execution systems now track output in real time, but supervisors run the shift: reallocating people when machines go down, enforcing safety, and answering for the numbers. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of First-Line Supervisors of Production Workers work are most exposed to AI?
Plan work schedules and production sequences and Inspect materials and products to detect defects show the strongest automation pressure in this model. Plan work schedules and production sequences and Inspect materials and products to detect defects are better treated as AI-augmented work.
What should First-Line Supervisors of Production Workers learn next?
Start with Production scheduling, Quality inspection, Safety enforcement. The most practical adjacent paths in this model are Plant Manager and Manufacturing Operations Analyst.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
OECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics