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Will AI replace Food Science Technicians?

Work with food scientists or technologists to perform standardized qualitative and quantitative tests to determine physical or chemical properties of food or beverage products. The percentage shown is a task-exposure model, not a prediction of certain job loss.

O*NET 30.3 · 19-4013.00 · modeled exposure, not guaranteed job loss
LOW TASK EXPOSURE
27%
Estimated share of representative tasks exposed to current AI capabilities.
Task automation shareⓘ
27%Automatable
Automatable27%
Augmentable40%
Hard to automate33%
Based on analysis of representative responsibilities and current AI capability maturity.
Category#
Healthcare
Clinical & Care
Modeled pay midpoint$
$67,100/yr
Directional estimate — verify locally
Time until impact⌁
6–10+ years
Earliest 2032 · widespread 2036+
Task-level replaceability ⓘ
Representative tasks ranked from highest to lowest AI exposure.
◇Taste or smell foods or beverages to ensure that flavors meet specifications or to select samples with specific characteristics.37%
⚙Measure, test, or weigh bottles, cans, or other containers to ensure that hardness, strength, or dimensions meet specifications.30%
✦Clinical accountability and hands-on care25%
▥Maintain records of testing results or other documents as required by state or other governing agencies.22%
✦Patient trust and complex diagnosis21%
Impact timeline ⓘ
How AI assistance may move from early support to wider adoption.
2032Next2036+
Light supportAI provides limited help with taste or smell foods or beverages to ensure that flavors meet specifications or to select samples with specific characteristics..
AugmentationTools improve productivity without owning outcomes.
Human-ledCore work stays anchored in clinical accountability and hands-on care.
6–10+ yearsdirectional confidence window
HOW AI CHANGES THIS JOBtyping the logic in plain English
01>Start with the real work done by Food Science Technicians.
02>AI can help with: Taste or smell foods or beverages to ensure that flavors meet specifications or to select samples with specific characteristics.
03>If a task is repetitive and easy to check, AI pressure goes up.
04>But a person is still needed for: Clinical accountability and hands-on care.
05>Likely result: AI mostly acts as a helper while the core job stays human-led.
06>Important: 27% is estimated task exposure—not a 27% chance of losing the job.
What AI can do
Taste or smell foods or beverages to ensure that flavors meet specifications or to select samples with specific characteristics.LOW MATCH
Measure, test, or weigh bottles, cans, or other containers to ensure that hardness, strength, or dimensions meet specifications.LOW MATCH
Maintain records of testing results or other documents as required by state or other governing agencies.LOW MATCH
How estimates work →
Your human moat
◆

Clinical accountability and hands-on care

HIGH MOAT

Combined with patient trust and complex diagnosis, this keeps a human in the loop.

Strength8.9
Similar-role comparison
RoleRisk
Food Science Technicians27%
Dental Assistants27%
Occupational Health and Safety Technicians27%
Registered Nurse (Bedside)26%
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Why this score?

✓The model evaluates 3 representative core tasks.
✓The core work depends on presence, dexterity, or accountability.
✓Occupation and task language comes from O*NET 30.3.
✓The strongest human advantage is clinical accountability and hands-on care.
Research basis

O*NET 30.3 occupation tasks plus the ILO 2025 exposure framework. Scores are directional estimates.

Read ILO research →
Data: O*NET 30.3 · Model framework: ILO 2025About O*NETShare report
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Dental Assistants · 27% exposureOccupational Health and Safety Technicians · 27% exposureRegistered Nurse (Bedside) · 26% exposure