All terms

AI Agents in Real Estate

AI agents in real estate are autonomous AI systems designed to execute specific commercial real estate workflows independently. Unlike chatbots that respond to prompts, AI agents take goals, plan multi-step approaches, access data sources, perform analysis, and produce structured deliverables. They function as virtual team members — site sourcers, analysts, underwriters, and researchers — that work alongside human professionals.

Types of CRE AI agents

The most common AI agent roles in CRE include: site sourcing agents (screening parcels against development criteria), due diligence agents (compiling environmental, zoning, and regulatory research), underwriting agents (building financial models from deal parameters), market research agents (synthesizing supply, demand, and demographic data), and reporting agents (assembling findings into institutional-grade deliverables).

How agents differ from tools

A CRE software tool requires a human to operate it — inputting data, configuring parameters, interpreting outputs. An AI agent takes a brief ('find data center sites in Virginia with 50+ MW available power') and autonomously plans its approach, accesses relevant data sources, performs analysis, and returns completed work product. The human's role shifts from operating the tool to reviewing and refining the agent's output.

The multi-agent model

Advanced CRE AI systems deploy multiple specialized agents that coordinate on complex workflows. A site selection project might involve a market research agent identifying target geographies, a site sourcing agent screening parcels, a due diligence agent evaluating top candidates, and an underwriting agent modeling financial returns — all working in parallel and sharing findings. This multi-agent approach mirrors how human development teams work, but at AI speed.