The Cost of a Slow Site-Selection Process
Industrial site selection at the $200k–$2M advisory engagement tier involves a genuine research problem: dozens of submarkets, varying labor availability, last-mile drive-time tradeoffs, and competing broker narratives about what's available. The traditional process depends heavily on broker-curated information and analyst-hours spent reconciling CoStar data with demand-node mapping. Delays cost money — lease rates in tight industrial markets don't stay flat while the analysis catches up, and missed site windows can push a fulfillment network buildout by a full quarter or more.
How an AI Agent Approaches Market Scoring
An AI Labor Company agent mines the existing site-criteria specification conversations and prior CBRE or JLL market-research deliverable threads that already exist in the operator's document environment. That institutional knowledge shapes a site-selection agent that pulls current CoStar industrial availabilities, scores candidate markets on labor-shed density and last-mile drive-time to the operator's demand nodes, and drafts the site-comparison matrix with the criteria weighting the VP Supply Chain has already defined. The short-list goes to the VP for approval before any site-tour commitments are made. Teams typically have this running in about 10 weeks, with broker engagement cost reductions in the range of 45–65%.
The Business Case: Speed and Lower Broker Dependency
The revenue mechanism here is growth velocity — a faster path from network-gap identification to lease execution means fulfillment capacity comes online sooner, supporting customer promise reliability during peak periods. For an e-commerce operator where fulfillment speed is a competitive variable, that lead time matters. Cost reduction on broker advisory fees is real but secondary; the more important outcome is that the internal supply chain team retains control of the analysis rather than delegating it entirely to advisors whose incentives aren't perfectly aligned.
Does the agent replace the broker relationship entirely?
No. The agent handles the data-intensive market scoring and matrix-drafting work that brokers typically bill for. The brokerage relationship for transaction execution and local market access still has value — the agent just reduces how much of the advisory spend goes toward work that can be systematized.
Can the agent handle custom scoring criteria, like proximity to specific carrier hubs or union-labor considerations?
Yes. The agent's scoring logic is built from the site-criteria specifications the supply chain team has already defined. Custom criteria get incorporated into the model rather than handled as exceptions.