AI & Real Estate: Beyond Generative
The latest "Generative AI for Real Estate" module highlights that the pace of AI adoption, not its direction, will dictate whether commercial real‑estate assets appreciate or depreciate. Fast‑feedback domains such as HVAC optimisation and lease abstraction are already transforming, while strategic areas with diffuse feedback lag behind. Enterprise‑scale AI now costs more in integration, data governance and change management than in raw inference. The shift from need‑driven to want‑driven demand forces owners to prioritize quality and flexibility to capture the emerging operational alpha.
Where’s the New Business?
The article introduces the H3 Provocation Framework, a five‑question tool designed to push AI initiatives in commercial real‑estate (CRE) beyond efficiency (H1) and capability (H2) into true transformation (H3). By applying the framework to workflows such as diligence, advisory, occupancy...
CRE: Constraints, Moats and Value
Wall Street wiped 12‑14% off the market caps of CBRE, JLL and Cushman & Wakefield after analysts warned that high‑fee, labor‑intensive CRE models are vulnerable to AI disruption. At the same time, Yardi’s research with AREF found only 45% of...
You're Probably Automating the Wrong Things
The commercial‑real‑estate (CRE) sector now has a structured tool called the CRE Automation Matrix, which classifies tasks by operational versus strategic nature and by verifiability. By mapping workflows onto four quadrants, the framework helps firms avoid low‑ROI automation and the...
