Systems Aministrators

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 5 task statements that define Systems Aministrators (ISCO-08 2522) score an average of 0.57 on a 0–1 exposure scale — more exposed than about 94% 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 3 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 5 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Recommending changes to improve systems and network configurations, and determining hardware or software requirements related to such changes;”

Scores 0.61 on the 2025 scale. The task of recommending changes to improve systems and network configurations involves a mix of analytical and technical skills to assess current setups and determine necessary adjustments for optimization. Generative AI can assist significantly by analyzing data, identifying patterns, and suggesting potential changes or optimizations within the network. However, the task also requires human judgment and expertise to account for nuanced environmental factors, strategic decisions, and the integration of new technologies. Semantically similar tasks in the context provided, such as "Diagnosing and optimizing the operation of computer equipment" (adjusted score: 0.55) and "Handling incidents and conducting intrusion analysis for teleinformatics systems" (adjusted score: 0.65), indicate a moderate to high potential for AI assistance, acknowledging the necessity for human oversight and intervention. Considering the task's nature and the technological infrastructure in a high-income country like Poland, where resources and AI tools are readily accessible, the adjusted score reflects a balance between the potential for automation provided by AI and the essential human input for strategic and situation-specific decision-making.

Moving fastest, 2023 → 2025

“Maintaining and administering computer networks and related computing environments including computer hardware, systems software, applications software and all configurations;”

Model capability on this task changed by +0.48 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 2522, 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.

No U.S. role resolves through the crosswalk for this occupation. Search the encyclopedia for the closest match →

In context

Part of the 2 - Professionals major group. Return to the full gradient to see how the whole group sits.

Systems Aministrators sit at the 94th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Systems Aministrators rank in the 94th 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 0.14 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Recommending changes to improve systems and network configurations, and determining hardware or software requirements related to such changes;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Systems Aministrators". https://singulariki.com/gradient/2522-systems-aministrators.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.