How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Record sales or delivery information on daily sales or delivery record.67
- Collect money from customers, make change, and record transactions on customer receipts.61
- Write customer orders and sales contracts according to company guidelines.58
- Listen to and resolve customers' complaints regarding products or services.57
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Drive trucks to deliver such items as food, medical supplies, or newspapers.01
- Maintain trucks and food-dispensing equipment and clean inside of machines that dispense food or beverages.02
- Record sales or delivery information on daily sales or delivery record.03
- Collect money from customers, make change, and record transactions on customer receipts.04
- Listen to and resolve customers' complaints regarding products or services.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Shipping, Receiving, and Inventory Clerks
Closely related work
Compare these careers →Couriers and Messengers
Closely related work
Compare these careers →Heavy and Tractor-Trailer Truck Drivers
Related work
Compare these careers →Customer Service Representatives
Shares some work
Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
