First-Line Supervisors of Material-Moving Machine and Vehicle Operators

Most exposed tasks

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

• Confer with customers, supervisors, contractors, or other personnel to exchange information or to resolve problems.75
• Plan work assignments and equipment allocations to meet transportation, operations or production goals.75
• Review orders, production schedules, blueprints, or shipping or receiving notices to determine work sequences and material shipping dates, types, volumes, or destinations.75

Augmentable tasks

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

• Examine, measure, or weigh cargo or materials to determine specific handling requirements.59
• Assist workers in tasks, such as loading vehicles.59
• Inspect or test materials, stock, vehicles, equipment, or facilities to ensure that they are safe, free of defects, and consistent with specifications.57

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 68 puts First-Line Supervisors of Material-Moving Machine and Vehicle Operators in the most-exposed quarter of analyzed occupations. In practice, exposure this high is about the mix: 16 of 20 analyzed tasks lean automatable, 4 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

Shown only when the target is at least 10 points lower under the same score version and skill overlap is at least 50%. These are adjacent roles with lower task exposure — not guaranteed “safe careers”.

Related roles

Adjacent by skills or family — no exposure claim implied.

• First-Line Supervisors of Helpers, Laborers, and Material Movers, Hand 63
• First-Line Supervisors of Production and Operating Workers 59
• First-Line Supervisors of Farming, Fishing, and Forestry Workers 48
• First-Line Supervisors of Office and Administrative Support Workers 76
• First-Line Supervisors of Housekeeping and Janitorial Workers 50
• First-Line Supervisors of Non-Retail Sales Workers 61

FAQ — First-Line Supervisors of Material-Moving Machine and Vehicle Operators

What does a score of 68 mean for a First-Line Supervisors of Material-Moving Machine and Vehicle Operators?

It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 68 on a 0–100 exposure scale — in the most-exposed quarter 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: Confer with customers, supervisors, contractors, or other personnel to exchange information or to resolve problems; Plan work assignments and equipment allocations to meet transportation, operations or production goals; Review orders, production schedules, blueprints, or shipping or receiving notices to determine work sequences and material shipping dates, types, volumes, or destinations. 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.