Will AI replace Quality Control Analysts?
Work in Quality Control Analysts sits in the in-between: AI reaches some of it (~52% in theory) but is only measured doing about 10% today — part human, part machine.
O*NET-SOC 19-4099
How your 30 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~52%). By late 2025, real-world AI use had reached about 10% of its task activity (growing but still limited). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
Don't trust a single AI-risk score here
For this job, the signals disagree sharply. AI's theoretical reach looks moderate (~52%), but real-world use is only ~10%, and how much AI "can" do shifts wildly by model — one 2026 study found the share of "high-risk" jobs swung 2.7% to 51.5% just by changing which AI did the rating. This page shows the spread instead of pretending there's one number.
See all 30 tasks, ratedBased on real task-level AI scores — click to collapse
- Complete documentation needed to support testing procedures, including data capture forms, equipment logbooks, or inventory forms.
- Write technical reports or documentation, such as deviation reports, testing protocols, and trend analyses.
- Write or revise standard quality control operating procedures.
- Perform validations or transfers of analytical methods in accordance with applicable policies or guidelines.
- Conduct routine and non-routine analyses of in-process materials, raw materials, environmental samples, finished goods, or stability samples.
- Interpret test results, compare them to established specifications and control limits, and make recommendations on appropriateness of data for release.
- Perform visual inspections of finished products.
- Compile laboratory test data and perform appropriate analyses.
- Identify and troubleshoot equipment problems.
- Investigate or report questionable test results.
- Monitor testing procedures to ensure that all tests are performed according to established item specifications, standard test methods, or protocols.
- Identify quality problems and recommend solutions.
- Participate in out-of-specification and failure investigations and recommend corrective actions.
- Supply quality control data necessary for regulatory submissions.
- Serve as a technical liaison between quality control and other departments, vendors, or contractors.
- Participate in internal assessments and audits as required.
- Evaluate analytical methods and procedures to determine how they might be improved.
- Collect geospatial data, using technologies such as aerial photography, light and radio wave detection systems, digital satellites, or thermal energy systems.
- Verify integrity and accuracy of data contained in remote sensing image analysis systems.
- Integrate remotely sensed data with other geospatial data.
- Consult with remote sensing scientists, surveyors, cartographers, or engineers to determine project needs.
- Adjust remotely sensed images for optimum presentation by using software to select image displays, define image set categories, or choose processing routines.
- Manipulate raw data to enhance interpretation, either on the ground or during remote sensing flights.
- Merge scanned images or build photo mosaics of large areas, using image processing software.
- Participate in the planning or development of mapping projects.
- Prepare documentation or presentations, including charts, photos, or graphs.
- Calibrate, validate, or maintain laboratory equipment.
- Ensure that lab cleanliness and safety standards are maintained.
- Receive and inspect raw materials.
- Train other analysts to perform laboratory procedures and assays.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.