Client Information Workers Not Elsewhere Classified

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 6 task statements that define Client Information Workers Not Elsewhere Classified (ISCO-08 4229) score an average of 0.42 on a 0–1 exposure scale — more exposed than about 78% 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 6 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Verifying the accuracy of information provided;”

Scores 0.60 on the 2025 scale. Verifying the accuracy of information provided as a task heavily involves analyzing data and ensuring its consistency and correctness, which are areas where Generative AI shows considerable potential. AI systems can aid in systematically checking data consistency against predefined standards, flagging anomalies, and even suggesting corrections automatically. Tasks like "Analyzing and verifying entered information and data" scored a 0.705, reflecting the high capability of AI to assist in data-related verification. However, full automation is limited by the need for context-specific judgment and interpretation, which often requires human insight, especially in complex or ambiguous scenarios. Additionally, "Confirming to the reporting person the acceptance of the alarm report" received a score of 0.385, demonstrating a moderate automation potential where human oversight is still necessary. Given the capabilities of AI in automating structured verification but recognizing the necessity of human involvement for nuanced judgment, especially in a well-equipped technological environment like Poland, the adjusted score for this task reasonably aligns at 0.55. This reflects a significant role for AI, complemented by human expertise, particularly where the task involves interpretation beyond mere data consistency checks.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 4229, 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.

• Eligibility Interviewers, Government Programs
• Information and Record Clerks, All Other
• Communications Equipment Operators, All Other

In context

Part of the 4 - Clerical support workers major group. Return to the full gradient to see how the whole group sits.

Client Information Workers Not Elsewhere Classified sit at the 78th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Client Information Workers Not Elsewhere Classified rank in the 78th 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 0.13 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Verifying the accuracy of information provided;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Client Information Workers Not Elsewhere Classified". https://singulariki.com/gradient/4229-client-information-workers-not-elsewhere-classified.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.