2025 Year in Review: L.D. Salmanson, Cherre

What transaction, project, or key moment best reflected the direction of the New York CRE market this year? 
2025 was the year the NYC market finally shifted from talking about AI to operationalizing it, and that exposed CRE’s biggest bottleneck: disconnected, low-trust data. The most defining moment wasn’t a single trade, but a wave of behind-the-scenes data-modernization efforts across major owners, managers, and brokerages. Several high-profile recaps and restructurings hinged on firms’ ability to deliver clean, connected, timely asset-level data. The message was clear: you can’t compete on AI with a broken data foundation. NYC entered a data-first era faster than any other market - a shift Cherre has long enabled.

What emerging trends or shifts will shape opportunities for you, your firm, or market sector in 2026? 
In 2026, regulators and limited partners will start asking hard questions about AI-driven valuations, underwriting decisions, and risk scoring. “The model said so” won’t cut it anymore. You’ll need to show lineage, prove data quality, and demonstrate governance. Most firms can’t do that today because their data lives in twenty disconnected systems. The firms that built proper infrastructure, that can trace every input and validate every output, will have a structural advantage. Everyone else will be retrofitting at exactly the wrong time. 

What accomplishment, milestone, project or transaction stood out for you or your firm in 2025? 
Cherre launched Agent STUDIO and the AI Agent Marketplace to show the industry what “doing AI right” looks like when it’s built on connected, trusted data. The real estate industry has been chasing AI like it’s magic, but AI is only as good as the data it runs on. Most firms have data scattered across dozens of systems that don’t talk to each other. So they end up with chatbots that hallucinate numbers or single-purpose tools that automate one thing badly. Cherre spent years doing the unglamorous work of connecting data, building Universal and Semantic Data Models, creating a Knowledge Graph that actually understands how real estate works. That foundation is what lets our clients deploy AI agents that know how lease expirations impact debt capacity or how market shifts affect portfolio risk. It’s not about the AI. It’s about finally having trustworthy data underneath it.