Construction Managers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 11 task statements that define Construction Managers (ISCO-08 1323) score an average of 0.34 on a 0–1 exposure scale — more exposed than about 62% 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 Minimal 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

“Preparing tenders and contract bids;”

Scores 0.46 on the 2025 scale. The task of preparing tenders and contract bids involves several aspects where Generative AI can assist significantly, such as structuring, drafting, and standardizing information based on existing templates and regulations. Tasks such as "Preparing technical documentation of the work performed as well as tender documentation" with a score of 0.515 and "Preparing protocols for the takeover of the treasury" with a score of 0.44 provide a relevant benchmark, as these tasks similarly involve document preparation and require some domain-specific knowledge. While AI can streamline the drafting and organization processes, human oversight remains crucial for strategic planning, legal compliance, and negotiation nuances, akin to tasks involving high customer or contractor interaction responsibility, which tend to score lower due to the interpersonal components. Given the potential for technology to automate repetitive parts and assist in detail verification through data analysis, an adjusted score of 0.475 reflects AI's ability to significantly reduce human workload in preparatory and drafting phases, while still requiring human expertise for final customization and comprehensive oversight. Additionally, operating in a high-income country like Poland further increases the potential for AI support due to robust digital infrastructure.

Moving fastest, 2023 → 2025

“Interpreting architectural drawings and specifications;”

Model capability on this task changed by +0.16 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 1323, 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.

• Construction Managers

In context

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

Construction Managers sit at the 62nd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Construction Managers rank in the 62nd 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 fell by 0.07 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Preparing tenders and contract bids;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Construction Managers". https://singulariki.com/gradient/1323-construction-managers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.