AI Land Banking Strategy
The Problem
“De-risk land banking with predictive, data-driven site selection”
Organizations face these key challenges:
1
Opaque entitlement and zoning outcomes causing costly land holds, re-trades, or write-offs
2
Fragmented data across brokers, municipalities, GIS layers, and internal deal notes leading to inconsistent underwriting
3
Inability to systematically rank and monitor thousands of parcels as infrastructure, policy, and demand conditions change
Impact When Solved
Parcel-level scoring of entitlement probability, timeline, and key drivers to prioritize the best land betsAutomated market and submarket monitoring with alerts for zoning changes, planning actions, and infrastructure investmentsOptimized capital allocation across markets and deal structures (options vs. fee simple) to improve returns and reduce downside risk