Commercial real estate has survived every major technology wave of the past three decades largely unchanged, with brokers still juggling five or six disconnected systems before making a single phone call in 2026, according to industry observers. Dan Mosher, Co-Founder and CEO of DealGround, explains that the industry's relationship-based nature, where deals were crafted over lunch or golf, created a culture of data hoarding where information became a strategic weapon. This cultural foundation shaped slow technology adoption, leading brokers to accumulate multiple point solutions that don't communicate with each other.
The industry's advanced brokers now navigate remarkably detailed yet cumbersome workflows, starting in one system, pulling data into another, sometimes using ChatGPT, dropping results into Google My Maps with color-coded pins, switching to different systems for contact information, and checking CRMs for previous interactions. According to Mosher, the core problem wasn't technology absence but rather that each tool performed one function well, forcing brokers to serve as connective tissue between all systems. This fragmentation created significant inefficiencies in an industry where timing and information advantage are critical to success.
The dynamic is now changing because commercial real estate's unstructured data—offering memorandums, Excel spreadsheets, lease documents, surveys, due diligence materials, property notes, and contact information—represents exactly what artificial intelligence was designed to handle. For the first time, the characteristics that made CRE difficult to digitize are the same characteristics that make it ideal for AI-powered transformation. The industry has been sitting on a mountain of messy, siloed, unstructured data for decades, and large language models excel at synthesizing exactly that kind of information.
DealGround was designed around this insight, creating a single platform where brokers, investors, and analysts can centralize private data, access public property and title records, and query everything through a single AI-powered interface. The platform aims to become the database of records, tracking everything happening with a property—new tenants, lease expirations, rent increases, loan maturity dates—in one place. As Mosher describes it, properties are living, breathing organisms, and platforms must move with them over time.
The third wave of CRE transformation isn't simply about adding AI features to existing workflows but about collapsing the entire technology stack. The envisioned future involves one system that knows everything a broker knows, surfaces the right insights at the right time, and frees professionals to focus on what humans do better than software: building relationships and closing deals. The goal is for brokers to spend more time on relationships and less on administrative legwork, with systems conducting research and flagging important events like lease expirations or loan maturities so brokers can contact owners with relevant, well-informed propositions.
After decades of industry lag, Mosher believes conditions for real transformation are finally in place with existing data and ready AI tools, and even traditional brokers are questioning whether better approaches exist. The transformation isn't about replacing brokers but giving them an unfair advantage in a competitive marketplace. For more information about how AI is transforming commercial real estate workflows, visit https://www.dealground.com.
