Door-to-door Salespersons

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Door-to-door Salespersons (ISCO-08 5243) score an average of 0.46 on a 0–1 exposure scale — more exposed than about 84% 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 2 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

“Compiling lists of prospective clients and calling on them to obtain new business;”

Scores 0.62 on the 2025 scale. The task of compiling lists of prospective clients and calling on them to obtain new business involves a mix of data gathering, analysis, and communication. Generative AI can significantly assist in automation aspects like data aggregation from various digital sources, identifying potential clients through predictive analytics, and even automating some parts of communication such as initial email outreach or appointment scheduling. However, the task also requires human intuition for understanding nuanced market dynamics and personal communication styles, which AI cannot fully replicate. In the provided context, similar tasks like "Compiling a phone database" scored around 0.61, reflecting the ability of AI to streamline data-heavy processes. Other related tasks such as scheduling meetings and developing commercial offers, which also involve strategic thinking and interpersonal skills, scored between 0.6 to 0.69, suggesting that AI can efficiently handle routine elements of strategic client engagement but not the personalized sales pitch that may be necessary. Given these comparisons and the technological environment in a high-income country like Poland, where digital tools are widely accessible, a score of 0.62 accurately encapsulates the blend of high AI assistance potential with essential human oversight for nuanced client engagement.

Moving fastest, 2023 → 2025

“Giving details of various goods or services and of terms of sale by visiting clients and potential clients in private homes;”

Model capability on this task changed by +0.17 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 5243, 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.

Door-to-door Salespersons sit at the 84th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Door-to-door Salespersons rank in the 84th 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 0.02 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Compiling lists of prospective clients and calling on them to obtain new business;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Door-to-door Salespersons". https://singulariki.com/gradient/5243-door-to-door-salespersons.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.