Information and Communications Technology Service Managers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 11 task statements that define Information and Communications Technology Service Managers (ISCO-08 1330) score an average of 0.44 on a 0–1 exposure scale — more exposed than about 82% 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 11 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Evaluating the organization's technology use and needs and recommending improvements such as hardware and software upgrades;”

Scores 0.56 on the 2025 scale. The task of evaluating an organization's technology use and recommending improvements, such as hardware and software upgrades, involves both strategic decision-making and data-driven analysis. Generative AI has a significant potential to support this task by analyzing usage patterns, identifying inefficiencies, and suggesting optimal hardware or software solutions based on data. This aligns with the role AI can play in tasks like diagnosing and optimizing computer equipment operations or managing data for decision-making processes. Semantically similar tasks, such as "Diagnosing and optimizing the operation of computer equipment" (adjusted score of 0.55) and "Recommending computer hardware and software suppliers to superiors" (adjusted score of 0.45), show a moderate level of automation potential due to the analytical and data processing aspects involved. However, the task at hand also requires strategic insight and understanding of organizational needs, suggesting a slightly higher reliance on human judgment than these similar tasks. Considering the capabilities of AI to automate data analysis and provide recommendations, combined with the need for human oversight in strategic decision-making, an adjusted automation score of 0.57 reflects AI's significant supportive role while acknowledging the ongoing necessity of human expertise in evaluating and recommending technological improvements. Additionally, the context of performing this task in a well-connected, high-income country like Poland supports a higher automation potential, given the robust technological infrastructure available.

Moving fastest, 2023 → 2025

“Overseeing the security of ICT systems;”

Model capability on this task changed by +0.31 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 1330, 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.

• Computer and Information Systems Managers

In context

Part of the 1 - Managers major group. Return to the full gradient to see how the whole group sits.

Information and Communications Technology Service Managers sit at the 82nd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Information and Communications Technology Service Managers rank in the 82nd 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 rose by 0.13 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Evaluating the organization's technology use and needs and recommending improvements such as hardware and software upgrades;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Information and Communications Technology Service Managers". https://singulariki.com/gradient/1330-information-and-communications-technology-service-managers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.