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Janitors And Building Cleaners

Based on 10 assessments · 1 from real users

8% Low risk

Average realistic automation risk across all Janitors And Building Cleaners profiles in the dataset.

Raw potential
13%
Realistic risk
8%
Research benchmark ?
3%

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 Janitors And Building Cleanerss score between 7% and 9%.

0% 50% 100%
p10 · 7%
11% · p90
On-screen work 1%

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

In-person + screen 4%

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

Computer + action 0%

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

Fully in-person 95%

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

3 synthetic profiles for a Janitors And Building Cleaners, ordered by automation exposure. Tab between them to see how task mix drives the score difference.

Task Time Type Exposure
Emptying trash bins and replacing liners in offices, restrooms, and public areas
23% AA 2%
Sweeping, mopping, and vacuuming floors in hallways, offices, and common areas to remove dirt and debris
20% AA 3%
Dusting and wiping down surfaces such as desks, tables, shelves, and window sills
18% AA 7%
Cleaning and disinfecting restrooms, including toilets, sinks, mirrors, and floors
18% AA 10%
Operating and maintaining cleaning equipment like floor buffers, carpet cleaners, and pressure washers
deep expertise
9% AA 4%
Reporting maintenance issues such as broken lights, leaky faucets, or damaged furniture to supervisors
4% AD 27%
Restocking supplies like soap, paper towels, and toilet paper in restrooms and kitchens
4% AA 13%
Interacting with building occupants to address cleaning requests or answer questions about facility upkeep
deep expertise
0% AA 4%

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