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AI Automation Index
Will AI Replace Quality Control Analysts?
Task-level automation exposure for Quality Control Analysts: 26 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
55%
weighted task index
26 of 26 tasks scored
Median Salary
$62,280 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Medium
73,910 people hold this job — size, not growth
Projected 2025–35
+4.4%
employment change
11,200 openings a year · BLS line item
Pay by state
BLS OEWS publishes 51 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$35,060 – $86,260
Highest medians
Oklahoma $86,260
District of Columbia $79,230
California $78,350
Washington $73,530
Alaska $70,700
Lowest medians
Puerto Rico $35,060
Wisconsin $47,210
Nebraska $48,640
Indiana $48,650
Texas $48,960
State figures come from the 19-4099 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 55%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 9%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 45%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 15%
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 42/100
Moderate
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
26 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) 54%
15 tasks
Medium exposure (≥ 35%) 23%
6 tasks
Low exposure (below 35%) 23%
5 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
#16980 · Core · 28% automatable
Conduct routine and non-routine analyses of in-process materials, raw materials, environmental samples, finished goods, or stability samples.
visual inspection — Quality testing of materials is hands-on inspection
Test quality of materials or finished products.
#16974 · Core · 70% automatable
Interpret test results, compare them to established specifications and control limits, and make recommendations on appropriateness of data for release.
data analysis — Interprets data; domain expert validates meaning
Interpret research or operational data.
#16978 · Core · 18% automatable
Calibrate, validate, or maintain laboratory equipment.
physical manipulation — Physical calibration of instruments requires hands
Calibrate scientific or technical equipment. Maintain laboratory or technical equipment.
#16961 · Core · 20% automatable
Ensure that lab cleanliness and safety standards are maintained.
visual inspection — Sanitation inspection requires on-site physical check
Inspect areas for compliance with sanitation standards.
#16956 · Core · 45% automatable
Perform visual inspections of finished products.
visual inspection — Material quality often needs hands-on or visual inspection
Evaluate quality of materials or products.
#16977 · Core · 82% automatable
Complete documentation needed to support testing procedures, including data capture forms, equipment logbooks, or inventory forms.
data analysis — Record research or operational data into schemas
Record research or operational data.
#16979 · Core · 80% automatable
Compile laboratory test data and perform appropriate analyses.
data analysis — Applies math/statistics to problems; human validates
Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields.
#16959 · Core · 18% automatable
Identify and troubleshoot equipment problems.
physical manipulation — Hands-on lab/technical equipment upkeep
Maintain laboratory or technical equipment.
#16964 · Core · 80% automatable
Write technical reports or documentation, such as deviation reports, testing protocols, and trend analyses.
text generation — Generate operational reports from structured data
Prepare operational reports.
#16973 · Core · 78% automatable
Investigate or report questionable test results.
data analysis — AI analyzes test results against criteria
Analyze test results.
#16972 · Core · 45% automatable
Monitor testing procedures to ensure that all tests are performed according to established item specifications, standard test methods, or protocols.
decision support — Conformance checking aided by AI, but on-site verification is human
Monitor operational procedures in technical environments to ensure conformance to standards.
#16975 · Core · 62% automatable
Identify quality problems and recommend solutions.
decision support — Drafts advice; accountability and context owned by human
Advise others on business or operational matters.
#16971 · Core · 68% automatable
Participate in out-of-specification and failure investigations and recommend corrective actions.
data analysis — Quantitative failure analysis; domain judgment needed
Conduct quantitative failure analyses of operational data.
#16967 · Core · 45% automatable
Receive and inspect raw materials.
visual inspection — Material quality often needs hands-on or visual inspection
Evaluate quality of materials or products.
#16955 · Core · 40% automatable
Train other analysts to perform laboratory procedures and assays.
interpersonal — Technical procedure training needs live demonstration and correction
Train personnel in technical or scientific procedures.
#16966 · Core · 70% automatable
Supply quality control data necessary for regulatory submissions.
text generation — Draft legal/regulatory docs; human verifies
Prepare information or documentation related to legal or regulatory matters.
#16957 · Core · 30% automatable
Serve as a technical liaison between quality control and other departments, vendors, or contractors.
interpersonal — Cross-department trust-building is relational human work
Develop collaborative relationships between departments or with external organizations.
#16965 · Core · 60% automatable
Write or revise standard quality control operating procedures.
text generation — AI drafts standards; committee consensus and authority human
Establish standards for products, processes, or procedures.
#16958 · Core · 50% automatable
Participate in internal assessments and audits as required.
decision support — Audit fieldwork and attestation remain human-owned
Conduct financial or regulatory audits.
#16970 · Core · 72% automatable
Perform validations or transfers of analytical methods in accordance with applicable policies or guidelines.
data analysis — Recommends analysis methods; human selects
Determine appropriate methods for data analysis.
#16976 · Core · 65% automatable
Evaluate analytical methods and procedures to determine how they might be improved.
decision support — Technology evaluation aided; strategic judgment human
Evaluate new technologies or methods.
#16969 · Supplemental · 70% automatable
Prepare or review required method transfer documentation including technical transfer protocols or reports.
text generation — Draft legal/regulatory docs; human verifies
Prepare information or documentation related to legal or regulatory matters.
#16968 · Supplemental · 85% automatable
Review data from contract laboratories to ensure accuracy and regulatory compliance.
data analysis — Data accuracy verification is rule-based and reliable
Verify accuracy of data.
#16962 · Supplemental · 65% automatable
Develop and qualify new testing methods.
text generation — AI drafts testing routines; engineer verifies coverage
Develop testing routines or procedures.
#16963 · Supplemental · 50% automatable
Coordinate testing with contract laboratories and vendors.
interpersonal — Cross-party coordination aided; humans own commitments
Coordinate activities with suppliers, contractors, clients, or other departments.
#16960 · Supplemental · 65% automatable
Evaluate new technologies and methods to make recommendations regarding their use.
decision support — New-tech advice needs organizational context judgment
Advise others on the development or use of new technologies.
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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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