Share and intensity of work current AI systems can materially affect.
Weighers, Measurers, Checkers, and Samplers AI displacement risk
Weighers, measurers, checkers, and samplers record the quantity, quality, and condition of materials moving through production and shipping. In-line scales, machine vision, and sensor telemetry now capture exactly these readings automatically — this is one of the clearest cases of instrumentation replacing a recording job.
Likely potential for exposed tasks to move to software after workflow integration.
The honest reading is high pressure: connected scales and vision systems do the measuring, and the data flows straight to the ERP. What remains is sample collection for lab analysis, exception inspection, and scale-house operation at sites that have not modernized.
Distribution
Where Weighers, Measurers, Checkers, and Samplers sits across 620 tracked roles
Displacement pressure 60 — higher than 88% 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.
18 O*NET task statements matched to SOC 43-5111. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $46,380 (May 2025, US national). The latest BLS row matched SOC 43-5111.
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 Weighers, Measurers, Checkers, and Samplers
SOC 43-5111 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 60/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
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.
O*NET task matches for Weighers, Measurers, Checkers, and Samplers
The current evidence import matched 18 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.
- Core task / ID 11380
Document quantity, quality, type, weight, test result data, and value of materials or products to maintain shipping, receiving, and production records and files.
- Core task / ID 11383
Weigh or measure materials, equipment, or products to maintain relevant records, using volume meters, scales, rules, or calipers.
- Core task / ID 11379
Collect or prepare measurement, weight, or identification labels and attach them to products.
- Core task / ID 11397
Examine products or materials, parts, subassemblies, and packaging for damage, defects, or shortages, using specification sheets, gauges, and standards charts.
- Core task / ID 11391
Signal or instruct other workers to weigh, move, or check products.
- Core task / ID 11386
Collect product samples and prepare them for laboratory analysis or testing.
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
Weigh and measure materials using scales and meters
Exposure 66, automation 46%, augmentation 40%.
O*NET evidence: Weigh or measure materials, equipment, or products to maintain relevant records, using ... (ID 11383)
Document quantity, quality, and test data
Exposure 68, automation 46%, augmentation 52%.
O*NET evidence: Document quantity, quality, type, weight, test result data, and value of materials or p... (ID 11380)
Examine products for damage, defects, or shortages
Exposure 48, automation 26%, augmentation 50%.
O*NET evidence: Examine products or materials, parts, subassemblies, and packaging for damage, defects,... (ID 11397)
Collect product samples for laboratory analysis
Exposure 40, automation 20%, augmentation 46%.
O*NET evidence: Collect product samples and prepare them for laboratory analysis or testing. (ID 11386)
Transition pathways
Adjacent moves that preserve existing skills
Quality Control Inspector
Training horizon: 3-6 months. Skill overlap 68. Wage preservation signal 116.
- Learn vision-system verification
- Own defect documentation
- Audit measurement systems
Logistics Data Coordinator
Training horizon: 3-6 months. Skill overlap 62. Wage preservation signal 112.
- Manage scale-system data
- Reconcile shipment records
- Serve production planners
Comparison guides
Compare the next move before you commit
Weighers, Measurers, Checkers, and Samplers to Quality Control Inspector
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Weighers, Measurers, Checkers, and Samplers into Quality Control Inspector.
Weighers, Measurers, Checkers, and Samplers to Logistics Data Coordinator
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Weighers, Measurers, Checkers, and Samplers into Logistics Data Coordinator.
What the AI risk score means for Weighers, Measurers, Checkers, and Samplers
The displacement pressure score for Weighers, Measurers, Checkers, and Samplers is 60. 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. Weigh and measure materials using scales and meters carries 46% automation pressure, while Document quantity, quality, and test data carries 52% 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: $46,380 (May 2025, US national). Employment context: Measurement-record role directly in sensor automation's path. Typical education: High school plus on-the-job training.
Wage vulnerability is 58, while transition feasibility is 60. 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.
- High displacement pressure
- Sensors capture readings automatically
- Sampling and exceptions remain human
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Weighers, Measurers, Checkers, and Samplers, 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.
Precision measurement
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.
Records documentation
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.
Sample collection
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 Quality Control Inspector, such as learn vision-system verification.
- By 90 days, compare internal openings and external postings for Quality Control Inspector or Logistics Data Coordinator and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Weighers, Measurers, Checkers, and Samplers
Will AI replace Weighers, Measurers, Checkers, and Samplers?
Weighers, measurers, checkers, and samplers record the quantity, quality, and condition of materials moving through production and shipping. In-line scales, machine vision, and sensor telemetry now capture exactly these readings automatically — this is one of the clearest cases of instrumentation replacing a recording job. 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 Weighers, Measurers, Checkers, and Samplers work are most exposed to AI?
Weigh and measure materials using scales and meters and Document quantity, quality, and test data show the strongest automation pressure in this model. Document quantity, quality, and test data and Examine products for damage, defects, or shortages are better treated as AI-augmented work.
What should Weighers, Measurers, Checkers, and Samplers learn next?
Start with Precision measurement, Quality inspection, Records documentation. The most practical adjacent paths in this model are Quality Control Inspector and Logistics Data Coordinator.
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