Mixing and Blending Machine Setters, Operators, and Tenders

Most exposed tasks

Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.

• Record operational or production data on specified forms.65
• Stop mixing or blending machines when specified product qualities are obtained and open valves and start pumps to transfer mixtures.63
• Tend accessory equipment, such as pumps or conveyors, to move materials or ingredients through production processes.63

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

• Mix or blend ingredients by starting machines and mixing for specified times.58
• Operate or tend machines to mix or blend any of a wide variety of materials, such as spices, dough batter, tobacco, fruit juices, chemicals, livestock feed, food products, color pigments, or explosive ingredients.58
• Dislodge and clear jammed materials or other items from machinery or equipment, using hand tools.58

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

The current data release does not distinguish durable tasks for this role.

Task exposure values and classifications come from the versioned data release — they are structured data, not model output. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 58 puts Mixing and Blending Machine Setters, Operators, and Tenders in the third quartile of analyzed occupations. In practice, exposure this high is about the mix: 8 of 20 analyzed tasks lean automatable, 12 augmentable, and 0 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

One next move: audit how much of your week sits in the exposed tasks above — then shift time toward the durable set or investigate the adjacent roles below.

Lower-exposure adjacent roles

No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.

Labor-market context

• $48,990median wage
• 94,920employed
• 8,800annual openings
• -6.7%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Related roles

Adjacent by skills or family — no exposure claim implied.

• Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders 53
• Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders 53
• Food Batchmakers 55
• Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders 52
• Machine Feeders and Offbearers 47
• Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders 53

FAQ — Mixing and Blending Machine Setters, Operators, and Tenders

What does a score of 58 mean for a Mixing and Blending Machine Setters, Operators, and Tenders?

It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 58 on a 0–100 exposure scale — in the third quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.

Which tasks in this role are most exposed to AI?

The highest-exposure tasks are: Record operational or production data on specified forms; Stop mixing or blending machines when specified product qualities are obtained and open valves and start pumps to transfer mixtures; Tend accessory equipment, such as pumps or conveyors, to move materials or ingredients through production processes. Exposure is scored per task from structured data, not generated by a language model.

Which parts of this job are most durable?

The current data release does not distinguish durable tasks for this role.

Is this score personalized to me?

No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.