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Do you agree with the AI automation risk score calculated for this occupation?
AI Automation Index
Will AI Replace Food Scientists and Technologists?
Task-level automation exposure for Food Scientists and Technologists: 13 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
48%
weighted task index
13 of 13 tasks scored
Median Salary
$88,720 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
13,060 people hold this job — size, not growth
Projected 2025–35
+6.2%
employment change
1,000 openings a year · BLS line item
Pay by state
BLS OEWS publishes 39 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$52,230 – $108,660
Highest medians
South Carolina $108,660
Missouri $105,930
New Jersey $104,340
Massachusetts $103,580
Florida $101,160
Lowest medians
Montana $52,230
Indiana $69,350
South Dakota $71,330
Nebraska $72,230
Utah $73,280
State figures come from the 19-1012 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 48%
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 24%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 0%
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 24/100
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
13 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) 38%
5 tasks
Medium exposure (≥ 35%) 45%
6 tasks
Low exposure (below 35%) 17%
2 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 →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- New 08/2025 · Occupational Expert
Test processing equipment to ensure products are produced according to specifications.
Constituent Tasks
#7494 · Core · 20% automatable
Inspect food processing areas to ensure compliance with government regulations and standards for sanitation, safety, quality, and waste management.
visual inspection — Sanitation inspection requires on-site physical check
Inspect areas for compliance with sanitation standards.
#7486 · Core · 45% automatable
Check raw ingredients for maturity or stability for processing, and finished products for safety, quality, and nutritional value.
visual inspection — Material quality often needs hands-on or visual inspection
Evaluate quality of materials or products.
#7489 · Core · 38% automatable
Study methods to improve aspects of foods, such as chemical composition, flavor, color, texture, nutritional value, and convenience.
data analysis — Formulation analysis aided; bench trials human
Research methods to improve food products.
#7492 · Core · 60% automatable
Develop food standards and production specifications, safety and sanitary regulations, and waste management and water supply specifications.
text generation — AI drafts standards; committee consensus and authority human
Establish standards for products, processes, or procedures.
#18612 · Core · 82% automatable
Stay up to date on new regulations and current events regarding food science by reviewing scientific literature.
information retrieval — AI can search and summarize literature, human curates
Review professional literature to maintain professional knowledge.
#7490 · Core · 38% automatable
Study the structure and composition of food or the changes foods undergo in storage and processing.
data analysis — Formulation analysis aided; bench trials human
Research methods to improve food products.
#7487 · Core · 60% automatable
Confer with process engineers, plant operators, flavor experts, and packaging and marketing specialists to resolve problems in product development.
decision support — Technical design collaboration aided; humans own decisions
Collaborate with technical specialists to resolve design or development problems.
#7485 · Core · 28% automatable
Test new products for flavor, texture, color, nutritional content, and adherence to government and industry standards.
visual inspection — Quality testing of materials is hands-on inspection
Test quality of materials or finished products.
#18611 · Core · 60% automatable
Develop new food items for production, based on consumer feedback.
decision support — Specs drafted; human validates feasibility
Develop specifications for new products or processes.
#7491 · Core · 38% automatable
Develop new or improved ways of preserving, processing, packaging, storing, and delivering foods, using knowledge of chemistry, microbiology, and other sciences.
data analysis — Formulation analysis aided; bench trials human
Research methods to improve food products.
#7488 · Core · 65% automatable
Evaluate food processing and storage operations and assist in the development of quality assurance programs for such operations.
decision support — Technology evaluation aided; strategic judgment human
Evaluate new technologies or methods.
#7493 · Core · 50% automatable
Demonstrate products to clients.
interpersonal — Client information exchange is live relational work
Confer with clients to exchange information.
#7495 · Core · 38% automatable
Seek substitutes for harmful or undesirable additives, such as nitrites.
data analysis — Formulation analysis aided; bench trials human
Research methods to improve food products.
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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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