Other

Warehouse Worker

Based on 10 assessments · 1 from real users

18% Low risk

Average realistic automation risk across all Warehouse Worker profiles in the dataset.

Raw potential
32%
Realistic risk
18%
Research benchmark ?
19%

Raw potential = I/O automation ceiling. Realistic risk = adjusted for informal knowledge and social context. Research benchmark: Eloundou et al. (2023)

Distribution across 10 profiles. Middle half of Warehouse Workers score between 17% and 20%.

0% 50% 100%
p10 · 12%
21% · p90
On-screen work 0%

Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.

In-person + screen 33%

Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.

Computer + action 42%

Computer input, real-world output — needs someone to act on it, not just software.

Fully in-person 24%

No computer required. Furthest from automation — the strongest human advantage.

3 synthetic profiles for a Warehouse Worker, ordered by automation exposure. Tab between them to see how task mix drives the score difference.

Task Time Type Exposure
Picking items from shelves based on order lists and packing them into boxes for shipment
23% DA 17%
Receiving and unloading goods from delivery trucks, scanning barcodes, and logging items into inventory system
deep expertise social element
20% AD 9%
Quality checking items for damage, expiration dates, or defects before packing
deep expertise social element
16% AD 15%
Labeling packages, applying shipping labels, and organizing items for shipment or internal transfer
16% DA 21%
Operating forklifts and pallet jacks to move heavy items and organize stock on shelves and pallets
deep expertise social element
12% AA 2%
Cleaning warehouse floors, organizing storage areas, and maintaining safe working conditions
some context needed
10% AA 1%

Work as a Warehouse Worker? Map your specific role.

Start assessment →