Real Estate Agents and Property Managers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Real Estate Agents and Property Managers (ISCO-08 3334) score an average of 0.35 on a 0–1 exposure scale — more exposed than about 65% 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 7 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Drawing up leasing and sale agreements and estimating costs;”

Scores 0.46 on the 2025 scale. The task of drawing up leasing and sale agreements and estimating costs primarily involves drafting legal documents, managing negotiations and understanding client-specific needs, which inherently require human oversight and legal expertise. Generative AI can assist in automating parts of these tasks, such as generating initial drafts, identifying relevant clauses, performing calculations, and suggesting terms based on historical data. However, the dynamic nature of negotiations, personalized adjustments, and complex legal contexts necessitate significant human involvement. Semantically similar tasks, such as “Conducting sales of valuable marks” and “Preparing bill of quantities and measurements” received adjusted scores of 0.38 and 0.40, respectively, indicating partial automation potential due to the need for human intervention in negotiation and complexity management. Considering the task's structured components amenable to automation, yet acknowledging the critical human oversight required, a score of 0.46 reflects the feasibility of Generative AI in aiding these processes within a high-income country like Poland, where technology infrastructure supports such integrations.

Moving fastest, 2023 → 2025

“Showing properties to be sold or leased to prospective buyers or tenants and explaining terms of sale or conditions of rent or lease;”

Model capability on this task changed by +0.13 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 3334, 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.

• Property, Real Estate, and Community Association Managers
• First-Line Supervisors of Non-Retail Sales Workers
• Real Estate Sales Agents
• Real Estate Brokers

In context

Part of the 3 - Technicians and associate professionals major group. Return to the full gradient to see how the whole group sits.

Real Estate Agents and Property Managers sit at the 65th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Real Estate Agents and Property Managers rank in the 65th 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 0.03 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Drawing up leasing and sale agreements and estimating costs;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Real Estate Agents and Property Managers". https://singulariki.com/gradient/3334-real-estate-agents-and-property-managers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.