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Will AI replace First-Line Supervisors of Food Preparation and Serving Workers?

Directly supervise and coordinate activities of workers engaged in preparing and serving food. The percentage shown is a task-exposure model, not a prediction of certain job loss.

O*NET 30.3 · 35-1012.00 · modeled exposure, not guaranteed job loss
LOW TASK EXPOSURE
20%
Estimated share of representative tasks exposed to current AI capabilities.
Task automation shareⓘ
20%Automatable
Automatable20%
Augmentable44%
Hard to automate36%
Based on analysis of representative responsibilities and current AI capability maturity.
Category#
Customer-Facing
Front line / Support
Modeled pay midpoint$
$81,500/yr
Directional estimate — verify locally
Time until impact⌁
6–10+ years
Earliest 2032 · widespread 2036+
Task-level replaceability ⓘ
Representative tasks ranked from highest to lowest AI exposure.
◇Resolve customer complaints regarding food service.30%
✦Human empathy and real-time de-escalation27%
⚙Train workers in food preparation, and in service, sanitation, and safety procedures.23%
✦Physical presence and relationship trust23%
▥Assign duties, responsibilities, and work stations to employees in accordance with work requirements.15%
Impact timeline ⓘ
How AI assistance may move from early support to wider adoption.
2032Next2036+
Light supportAI provides limited help with resolve customer complaints regarding food service..
AugmentationTools improve productivity without owning outcomes.
Human-ledCore work stays anchored in human empathy and real-time de-escalation.
6–10+ yearsdirectional confidence window
HOW AI CHANGES THIS JOBtyping the logic in plain English
01>Start with the real work done by First-Line Supervisors of Food Preparation and Serving Workers.
02>AI can help with: Resolve customer complaints regarding food service.
03>If a task is repetitive and easy to check, AI pressure goes up.
04>But a person is still needed for: Human empathy and real-time de-escalation.
05>Likely result: AI mostly acts as a helper while the core job stays human-led.
06>Important: 20% is estimated task exposure—not a 20% chance of losing the job.
What AI can do
Resolve customer complaints regarding food service.LOW MATCH
Train workers in food preparation, and in service, sanitation, and safety procedures.LOW MATCH
Assign duties, responsibilities, and work stations to employees in accordance with work requirements.LOW MATCH
How estimates work →
Your human moat
◆

Human empathy and real-time de-escalation

HIGH MOAT

Combined with physical presence and relationship trust, this keeps a human in the loop.

Strength8.8
Similar-role comparison
RoleRisk
First-Line Supervisors of Food Preparation and Serving Workers20%
Community Health Workers20%
First-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services20%
Mental Health and Substance Abuse Social Workers20%
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Why this score?

✓The model evaluates 3 representative core tasks.
✓The core work depends on presence, dexterity, or accountability.
✓Occupation and task language comes from O*NET 30.3.
✓The strongest human advantage is human empathy and real-time de-escalation.
Research basis

O*NET 30.3 occupation tasks plus the ILO 2025 exposure framework. Scores are directional estimates.

Read ILO research →
Data: O*NET 30.3 · Model framework: ILO 2025About O*NETShare report
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Community Health Workers · 20% exposureFirst-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services · 20% exposureMental Health and Substance Abuse Social Workers · 20% exposure