Government

Customs Officer

Based on 20 assessments

34% Moderate risk

Average realistic automation risk across all Customs Officer profiles in the dataset.

Raw potential
59%
Realistic risk
34%
Research benchmark ?
40%

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

Distribution across 20 profiles. Middle half of Customs Officers score between 30% and 37%.

0% 50% 100%
p10 · 26%
39% · p90
On-screen work 34%

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

In-person + screen 54%

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 12%

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

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

Task Time Type Exposure
Interviewing travelers and traders to assess risk, verify declarations, and gather information
deep expertise social element
36% AD 16%
Processing import/export documentation, tariff classifications, and duty calculations
deep expertise social element
28% DD 31%
Inspecting cargo, containers, and baggage for prohibited items, contraband, and customs violations
deep expertise social element
10% AD 19%
Resolving disputes, addressing discrepancies, and making judgment calls on borderline cases
deep expertise
8% AD 7%
Operating customs management systems to enter data, track shipments, and generate reports
8% DD 86%
Communicating with importers, brokers, and other agencies to clarify rules and coordinate enforcement
some context needed
4% AD 16%
Conducting physical searches and using inspection equipment (scanners, detection devices)
3% AA 5%

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