Street Food Salespersons

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 5 task statements that define Street Food Salespersons (ISCO-08 5212) score an average of 0.22 on a 0–1 exposure scale — more exposed than about 40% 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 Not exposed 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 5 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Displaying and selling food and drinks and accepting payment.”

Scores 0.36 on the 2025 scale. The task of displaying and selling food and drinks and accepting payment involves a mixture of physical and customer-interactive elements. This blend places the task somewhere between those with higher automation potential due to routine data processing and those that require significant human interaction. Similar tasks from the provided context, such as "Collecting payments for sold products" and "Accepting payments for sold goods and issuing receipts", received adjusted scores of 0.375 and 0.152 respectively. Both involve some kind of transactional process but differ in complexity due to the necessity of handling physical items and interacting with customers, which is not easily automated by AI. Generative AI can assist with digital aspects of the task, such as processing card payments or keeping electronic records, but it lacks the capability to entirely automate the interaction-intensive and physical handling components present in this task. AI could potentially support the task through automated systems for order taking and inventory management, yet human intervention is crucial for quality assurance, customer service, and managing cash transactions or dealing with exceptions. Considering the nature of the task and technological context, the adjusted score of 0.375 aptly reflects the significant role AI can play without ignoring the indispensable human elements necessary for performing these tasks effectively.

Moving fastest, 2023 → 2025

“Preparing, either beforehand or on the spot, food and drinks for sale;”

Model capability on this task changed by +0.11 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 5212, 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.

• Food Servers, Nonrestaurant
• Door-to-Door Sales Workers, News and Street Vendors, and Related Workers

In context

Part of the 5 - Service and sales workers major group. Return to the full gradient to see how the whole group sits.

Street Food Salespersons sit at the 40th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Street Food Salespersons rank in the 40th 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 rose by 0.04 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Displaying and selling food and drinks and accepting payment.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Street Food Salespersons". https://singulariki.com/gradient/5212-street-food-salespersons.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.