Domestic Cleaners and Helpers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Domestic Cleaners and Helpers (ISCO-08 9111) score an average of 0.14 on a 0–1 exposure scale — more exposed than about 15% 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 7 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Purchasing food and various other household supplies;”

Scores 0.30 on the 2025 scale. The task of purchasing food and various other household supplies involves several elements suitable for automation, such as scheduling purchases or analyzing purchase data to identify trends and recommend products. This is comparable to "Replenishing the assortment of goods for sale" (0.175), where generative AI can assist with optimizing inventory but cannot replace physical actions or complex decisions involved in transaction execution. Moreover, tasks like "Making independent purchases on commission" (0.525) reflect that while AI can support decision-making and information retrieval, human judgment and interaction are still crucial. Considering the physical and interactive nature of the task and recognizing the supportive role AI can play, the potential for automation is moderate, but not high. Thus, in the context of Poland, where access to technology is extensive, an adjusted score of 0.25 reflects automation capabilities balanced with the continued need for human involvement in decision-making and execution.

Moving fastest, 2023 → 2025

“Purchasing food and various other household supplies;”

Model capability on this task changed by +0.05 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 9111, 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.

• Maids and Housekeeping Cleaners

In context

Part of the 9 - Elementary occupations major group. Return to the full gradient to see how the whole group sits.

Domestic Cleaners and Helpers sit at the 15th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Domestic Cleaners and Helpers rank in the 15th 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 0.00 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Purchasing food and various other household supplies;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Domestic Cleaners and Helpers". https://singulariki.com/gradient/9111-domestic-cleaners-and-helpers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.