Not Very Resilient

Last Update: 10/7/2026

AI Resilience Score for Separating/Filtering/Still:

31.9%

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 separating, filtering, and still machine operation 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 separating, filtering, and still machine operators, five of eight sources had data. Exposure sources were split: Microsoft saw the hands-on monitoring work staying human, while Will Robots Take My Job flagged high AI risk and our model landed in the middle. Weak hiring and pay outlooks pulled the score down, landing this role at "Not Very Resilient." Medium confidence reflects the missing sources.

AI Resilience Report forSeparating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders

$51,610 median salary•5,200 annual openings•SOC Code: 51-9012.00

Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders are less resilient to AI impacts than most occupations, according to our analysis of 5 sources.

This career gets a "Not Very Resilient" rating because AI and automation are taking over many of the core tasks that operators used to own, including monitoring equipment, adjusting controls, predicting maintenance needs, and keeping processes on target through multivariable control systems. Sensors, remote controls, and AI tools can now do much of the watching, listening, and adjusting that field operators once handled by hand and instinct.

Learn more about how you can thrive in this position

This role is not very resilient

This career gets a "Not Very Resilient" rating because AI and automation are taking over many of the core tasks that operators used to own, including monitoring equipment, adjusting controls, predicting maintenance needs, and keeping processes on target through multivariable control systems. Sensors, remote controls, and AI tools can now do much of the watching, listening, and adjusting that field operators once handled by hand and instinct.

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Analysis of current AI resilience

Separating/Filtering/Still

Updated quarterly

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Latest AI news for Separating/Filtering/Still

The recommended articles highlight the evolving role of AI in the career of Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders. For instance, one article notes a projected -4% job decline due to AI-enhanced automation, emphasizing the need for workers to adapt. Another article indicates a 59% AI risk score for this role, suggesting that while automation will impact entry-level positions, senior roles may remain stable. Understanding these trends can help students build resilience in their career paths by focusing on skills that complement AI advancements.

More Career Info

Career: Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders

They operate machines to clean and separate materials, ensuring products are purified and ready for use in various industries.

Employment & Wage Data

Median Wage

$51,610

Jobs (2025)

61,400

Growth (2025-35)

-5.7%

Annual Openings

5,200

Education

High school diploma or equivalent

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

85% ResilienceCore Task

Install, maintain, or repair hoses, pumps, filters, or screens to maintain processing equipment, using hand tools.

2

83% ResilienceCore Task

Assemble fittings, valves, bowls, plates, disks, impeller shafts, or other parts to prepare equipment for operation.

3

82% ResilienceCore Task

Connect pipes between vats and processing equipment.

4

80% ResilienceCore Task

Remove clogs, defects, or impurities from machines, tanks, conveyors, screens, or other processing equipment.

5

78% ResilienceCore Task

Clean or sterilize tanks, screens, inflow pipes, production areas, or equipment, using hoses, brushes, scrapers, or chemical solutions.

6

67% ResilienceSupplemental

Remove full containers from discharge outlets and replace them with empty containers.

7

65% ResilienceCore Task

Dump, pour, or load specified amounts of refined or unrefined materials into equipment or containers for further processing or storage.

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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