Somewhat Resilient

Last Update: 10/7/2026

AI Resilience Score for Food/Tobacco Machine Oper.:

35.0%

Median Score

Meaningful human contribution

Med

Long-term employer demand

Low

Sustained economic opportunity

Low

Our confidence in this score:
Medium

Methodology and Scoring Rationale

To score how resilient food and tobacco machine operating is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from five AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, Will Robots Take My Job, and OpenAI Signals. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For food and tobacco machine operators, five of eight sources had data. AI exposure sources split: Microsoft saw the work as human-centered, while AI Resilience Model and Will Robots Take My Job flagged high automation risk, keeping confidence at medium. Weak hiring and pay projections pulled the score down, landing this role at "Somewhat Resilient."

AI Resilience Report forFood and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders

$44,810 median salary•2,500 annual openings•SOC Code: 51-3091.00

Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders are somewhat less resilient to AI impacts than most occupations, according to our analysis of 5 sources.

This career sits in the "Somewhat Resilient" category because AI is genuinely changing a meaningful chunk of the day-to-day work, like monitoring temperatures, tracking batches, and spotting quality issues, but it has not replaced the human role entirely. Tasks that once kept operators busy watching dials and recording data by hand are increasingly handled by automated systems, so the job is shifting rather than disappearing.

Learn more about how you can thrive in this position

This role is somewhat resilient

This career sits in the "Somewhat Resilient" category because AI is genuinely changing a meaningful chunk of the day-to-day work, like monitoring temperatures, tracking batches, and spotting quality issues, but it has not replaced the human role entirely. Tasks that once kept operators busy watching dials and recording data by hand are increasingly handled by automated systems, so the job is shifting rather than disappearing.

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Analysis of current AI resilience

Food/Tobacco Machine Oper.

Updated quarterly

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More Career Info

Career: Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders

They operate machines to roast, bake, or dry food and tobacco products, ensuring they are properly processed and ready for packaging.

Employment & Wage Data

Median Wage

$44,810

Jobs (2025)

21,600

Growth (2025-35)

+0.4%

Annual Openings

2,500

Education

No formal educational credential

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

72% ResilienceSupplemental

Install equipment, such as spray units, cutting blades, or screens, using hand tools.

2

70% ResilienceSupplemental

Clear or dislodge blockages in bins, screens, or other equipment, using poles, brushes, or mallets.

3

65% ResilienceCore Task

Observe, feel, taste, or otherwise examine products during and after processing to ensure conformance to standards.

4

65% ResilienceSupplemental

Clean equipment with steam, hot water, and hoses.

5

62% ResilienceSupplemental

Push racks or carts to transfer products to storage, cooling stations, or the next stage of processing.

6

62% ResilienceSupplemental

Smooth out products in bins, pans, trays, or conveyors, using rakes or shovels.

7

60% ResilienceCore Task

Fill or remove product from trays, carts, hoppers, or equipment, using scoops, peels, or shovels, or by hand.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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