Mail Clerks and Mail Machine Operators, Except Postal Service
Mail Clerks and Mail Machine Operators, Except Postal Service — AI exposure, safer roles, and a pivot plan.
Also known as: Express Clerk · Dead Mail Checker · Direct Mail Clerk · Distribution Clerk · Advertising Inserter · Addressograph Operator
This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.
Most exposed tasks
Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.
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Clear jams in sortation equipment.86
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Sort and route incoming mail, and collect outgoing mail, using carts as necessary.85
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Contact delivery or courier services to arrange delivery of letters and parcels.75
Augmentable tasks
Work where AI assists rather than replaces — the productivity frontier of this role.
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Release packages or letters to customers upon presentation of written notices or other identification.57
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Inspect mail machine output for defects and determine how to eliminate causes of any defects.55
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 Mail Clerks and Mail Machine Operators, Except Postal Service in the most-exposed quarter of analyzed occupations. In practice, exposure this high is about the mix: 18 of 20 analyzed tasks lean automatable, 2 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
- $39,280median wage
- 55,230employed
- 6,900annual openings
- -6.7%projected growth
Context only — labor statistics are not inputs to the exposure score. See methodology.
Your week probably doesn’t match the average
This page scores the occupation. The $9 Personalized Risk & Action Report scores your task mix — paste what you actually do and get your own score, confidence level, task matrix, human moat, and a 7/30/90-day plan.
Personalize my result — $9Related roles
Adjacent by skills or family — no exposure claim implied.
FAQ — Mail Clerks and Mail Machine Operators, Except Postal Service
- What does a score of 68 mean for a Mail Clerks and Mail Machine Operators, Except Postal Service?
- 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: Clear jams in sortation equipment; Sort and route incoming mail, and collect outgoing mail, using carts as necessary; Contact delivery or courier services to arrange delivery of letters and parcels. 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.
Score version jr-v1 · data release 2026.07.11-r1 · updated 2026-07-11 · baseline mapping: 20 of 20 tasks carry source-level provenance · methodology