Customs and Border Inspectors

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 8 task statements that define Customs and Border Inspectors (ISCO-08 3351) score an average of 0.32 on a 0–1 exposure scale — more exposed than about 60% of the 427 placed occupations. Roughly 0% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Minimal band.

Exposure is task overlap, not a verdict. A high score means a generative-AI model can do part of the content of these tasks — it says nothing about whether the work is automated, whether anyone uses AI for it today, or whether jobs are lost. The gradient is scored on the international ISCO-08 system; the rest of Singulariki is U.S. O*NET/SOC, bridged below by an approximate, many-to-many crosswalk.

How its tasks split across the gradient

Each of the 8 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Performing related administrative tasks to record findings, transactions, violations and determinations;”

Scores 0.53 on the 2025 scale. The task involves performing administrative tasks related to recording findings, transactions, violations, and determinations, which align with structured data processing and compliance tasks. In the provided context, tasks such as "Conducting administrative proceedings for check-out, check-in, and revocation of material-technical activities" (score: 0.45) and "Storing and maintaining a register of found items" (score: 0.375) offer insights into the overlap in procedural and documentation-based tasks. These tasks indicate a moderate potential for automation as Generative AI can assist in data entry, preliminary analysis, and generating documentation due to its proficiency in handling repetitive and rule-based processes. However, the need for human oversight persists for nuanced decision-making, interpretation of complex situations, and ensuring regulatory compliance. In a high-income country like Poland, where digital infrastructure supports the integration of AI technologies, this increases the task's automation potential. Therefore, an adjusted score of 0.5 reflects this balance between tasks that are more procedural with limited human intervention and those requiring human oversight for accurate outcomes.

Moving fastest, 2023 → 2025

“Inspecting the luggage of persons crossing national borders to ensure that it conforms to government rules and regulations concerning import or export of goods and currencies;”

Model capability on this task changed by +0.20 in two years — the gradient is not static, it is filling in.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 3351, biggest by employment first, via the published (approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 correspondence. These are the closest U.S. matches — not an asserted one-to-one identity.

• Police and Sheriff's Patrol Officers
• Customs and Border Protection Officers
• Compliance Officers
• Environmental Compliance Inspectors
• Equal Opportunity Representatives and Officers
• Government Property Inspectors and Investigators
• Coroners
• Regulatory Affairs Specialists

In context

Part of the 3 - Technicians and associate professionals major group. Return to the full gradient to see how the whole group sits.

Customs and Border Inspectors sit at the 60th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Customs and Border Inspectors rank in the 60th percentile for GenAI task exposure — overlap with what generative AI can attempt, not a projection of displacement. (ILO / Gmyrek et al. (2025) GenAI exposure gradient)
• About 0% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure fell by 0.00 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Performing related administrative tasks to record findings, transactions, violations and determinations;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Customs and Border Inspectors". https://singulariki.com/gradient/3351-customs-and-border-inspectors.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.