The Task Exposure Indexv2026.Q3
Occupation · SOC 51-3092.00 · Job Zone 2

AI exposure: Food Batchmakers

Set up and operate equipment that mixes or blends ingredients used in the manufacturing of food products. Includes candy makers and cheese makers.

Reading this score

computed

At 18.9% of weighted task load, Food Batchmakers sits at the 33th percentile, below the point where a job's centre of gravity has moved. 67.6% of what this role does is untouched, meaning current systems cannot produce that work at all, whatever the commercial incentive.

What holds the line here is embodiment. Across this occupation's 25 tasks it averages 2.48 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.

The most exposed thing this job does is Record production and test data for each food product batch, at 73.3%. The least is Homogenize or pasteurize material to prevent separation or to obtain prescribed butterfat..., at 0.0%. A gap of 73.3% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.

Within production occupations, this one is more exposed than most. The median across the 107 roles in the group is 16.1%, and only 37 of them score higher than this. Occupational families are not uniform, and the spread inside them is often wider than the gap between them.

What would move this score. Of 25 tasks, 6 are currently banded exposed, 1 assisted and 18 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.

Where the score comes from

judged

Every task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.

DimensionMeanScale
Capability1.220-4
Embodiment2.480-3
Presence0.580-3
Accountability0.880-3
Context1.220-3
Verification cost1.120-3

Task by task

25 tasks, O*NET 31.0
TaskExposedAssistedUntouchedImportanceBand
Record production and test data for each food product batch, such as the ingredients used, temperature, test results, and time cycle.73.3%26.7%0.0%4.77exposed
Determine mixing sequences, based on knowledge of temperature effects and of the solubility of specific ingredients.40.0%35.0%25.0%4.51exposed
Modify cooking and forming operations based on the results of sampling processes, adjusting time cycles and ingredients to achieve desired qualities, such as firmness or texture.40.0%35.0%25.0%4.38exposed
Formulate or modify recipes for specific kinds of food products.40.0%35.0%25.0%4.28exposed
Observe gauges and thermometers to determine if the mixing chamber temperature is within specified limits, and turn valves to control the temperature.39.6%22.9%37.5%4.47exposed
Observe and listen to equipment to detect possible malfunctions, such as leaks or plugging, and report malfunctions or undesirable tastes to supervisors.35.4%27.1%37.5%4.50exposed
Select and measure or weigh ingredients, using English or metric measures and balance scales.23.8%13.8%62.5%4.55untouched
Give directions to other workers who are assisting in the batchmaking process.20.0%30.0%50.0%4.56assisted
Fill processing or cooking containers, such as kettles, rotating cookers, pressure cookers, or vats, with ingredients, by opening valves, by starting pumps or injectors, or by hand.17.5%7.5%75.0%4.53untouched
Mix or blend ingredients, according to recipes, using a paddle or an agitator, or by controlling vats that heat and mix ingredients.16.7%8.3%75.0%4.61untouched
Press switches and turn knobs to start, adjust, and regulate equipment, such as beaters, extruders, discharge pipes, and salt pumps.16.7%8.3%75.0%4.53untouched
Operate refining machines to reduce the particle size of cooked batches.16.7%8.3%75.0%4.29untouched
Inspect vats after cleaning to ensure that fermentable residue has been removed.13.3%11.7%75.0%4.61untouched
Examine, feel, and taste product samples during production to evaluate quality, color, texture, flavor, and bouquet, and document the results.10.0%15.0%75.0%4.28untouched
Test food product samples for moisture content, acidity level, specific gravity, or butter-fat content, and continue processing until desired levels are reached.10.0%15.0%75.0%4.66untouched
Grade food products according to government regulations or according to type, color, bouquet, and moisture content.10.0%15.0%75.0%4.33untouched
Set up, operate, and tend equipment that cooks, mixes, blends, or processes ingredients in the manufacturing of food products, according to formulas or recipes.7.5%5.0%87.5%4.65untouched
Inspect and pack the final product.7.5%5.0%87.5%4.16untouched
Clean and sterilize vats and factory processing areas.0.0%0.0%100.0%4.73untouched
Follow recipes to produce food products of specified flavor, texture, clarity, bouquet, or color.0.0%0.0%100.0%4.56untouched
Turn valve controls to start equipment and to adjust operation to maintain product quality.0.0%0.0%100.0%4.40untouched
Manipulate products, by hand or using machines, to separate, spread, knead, spin, cast, cut, pull, or roll products.0.0%0.0%100.0%4.49untouched
Cool food product batches on slabs or in water-cooled kettles.0.0%0.0%100.0%4.46untouched
Place products on carts or conveyors to transfer them to the next stage of processing.0.0%0.0%100.0%4.35untouched
Homogenize or pasteurize material to prevent separation or to obtain prescribed butterfat content, using a homogenizing device.0.0%0.0%100.0%4.33untouched

Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.

Occupations either side of this one

The four closest scores in the same occupational family, then the four closest anywhere in the index.

Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.

What this means in practice

Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.