Food Servers, Nonrestaurant
Food Servers, Nonrestaurant — AI exposure, safer roles, and a pivot plan.
Also known as: Curber · Car Hop · Boat Hop · Curb Hop · Food Porter · Food Runner
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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Record amounts and types of special food items served to customers.60
Augmentable tasks
Work where AI assists rather than replaces — the productivity frontier of this role.
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Monitor food distribution, ensuring that meals are delivered to the correct recipients and that guidelines, such as those for special diets, are followed.46
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Monitor food preparation or serving techniques to ensure that proper procedures are followed.46
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Determine where patients or patrons would like to eat their meals and help them get situated.44
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 41 puts Food Servers, Nonrestaurant in the second quartile of analyzed occupations. In practice, exposure this level is about the mix: 1 of 14 analyzed tasks lean automatable, 13 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: adopt AI deliberately on the augmentable tasks and build visible evidence of the durable ones.
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”.
Dining Room and Cafeteria Attendants and Bartender Helpers
27 ▼ 14 pts lower
Skill overlap ≈ 80% · Related O*NET role; Dining Room and Cafeteria Attendants and Bartender Helpers is an adjacent path (Moderate band).
Food Preparation Workers
30 ▼ 11 pts lower
Skill overlap ≈ 64% · Related O*NET role; Food Preparation Workers is an adjacent path (Elevated band).
Labor-market context
- $35,360median wage
- 293,900employed
- 48,000annual openings
- +2.9%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 — Food Servers, Nonrestaurant
- What does a score of 41 mean for a Food Servers, Nonrestaurant?
- It means that, weighted across the 14 tasks we analyzed for this role, the task mix sits at 41 on a 0–100 exposure scale — in the second 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 amounts and types of special food items served to customers. 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: 14 of 14 tasks carry source-level provenance · methodology