Stall and Market Salespersons

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Stall and Market Salespersons (ISCO-08 5211) score an average of 0.35 on a 0–1 exposure scale — more exposed than about 64% of the 427 placed occupations. Roughly 100% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Gradient 1 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 7 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Keeping accounts and maintaining a record of stock levels.”

Scores 0.60 on the 2025 scale. Keeping accounts and maintaining a record of stock levels involves significant data management and record-keeping, activities where Generative AI can significantly contribute by automating repetitive tasks such as data entry, updating inventory levels, and generating reports. This task is semantically similar to "Maintaining necessary documentation," "Preparing sales registers," "Monitoring warehouse inventory," and "Maintaining a register of contractors," all of which have automation scores ranging from 0.35 to 0.69, indicating varying automation potentials depending on the complexity and need for human oversight. Compared to tasks that require more physical interaction or nuanced judgment, this task primarily involves structured data handling, suggesting a moderate level of automation potential. The adjusted score of 0.45 reflects this moderate potential, acknowledging AI's capability to streamline and efficiently manage these aspects while still considering the necessity for human intervention in handling exceptions, ensuring compliance, and making judgment calls in dynamic situations. The high access to digital tools in Poland supports this level of automation potential, enhancing task efficiency.

Moving fastest, 2023 → 2025

“Buying or contracting a regular supply of goods to be sold from wholesale suppliers or directly from producers;”

Model capability on this task changed by +0.13 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 5211, 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.

• 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.

Stall and Market Salespersons sit at the 64th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Stall and Market Salespersons rank in the 64th 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 100% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure fell by 0.04 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Keeping accounts and maintaining a record of stock levels.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Stall and Market Salespersons". https://singulariki.com/gradient/5211-stall-and-market-salespersons.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.