Commercial real estate has consistently lagged behind other industries in adopting technological innovations, maintaining largely unchanged workflows through multiple digital revolutions. According to Dan Mosher, Co-Founder and CEO of DealGround, this resistance stems from the industry’s relationship-based nature where data has historically served as a strategic currency rather than a shared resource. ‘Commercial real estate is, at its core, a relationship-based industry,’ Mosher explains. ‘Deals were crafted over lunch, during golf, over drinks. It never had a centralized exchange like the stock market. That meant data was a currency. He who had the data nobody else had held a strategic weapon.’
This culture of data hoarding created what Mosher calls ‘The Five-System Problem,’ where brokers routinely navigate between multiple disconnected tools to complete basic tasks. Advanced brokers might start in one system, pull data into another, sometimes run it through ChatGPT, drop results into a Google My Maps with color-coded pins, switch to a different system to get an owner’s phone number, and then open their CRM to check previous communications. This fragmented approach has persisted despite decades of technological advancement because each tool addressed specific needs without integrating with others.
The current transformation differs fundamentally from previous technology waves because artificial intelligence is uniquely suited to handle commercial real estate’s particular data challenges. ‘The unstructured data that defines CRE – offering memorandums, excel spreadsheets, lease documents, surveys, due diligence materials, property notes, contact information – that’s almost exactly what AI was made to handle,’ Mosher says. ‘The industry has been sitting on a mountain of messy, siloed, unstructured data for decades. Large language models are extraordinarily good at synthesizing exactly that kind of information.’ For the first time, the characteristics that made commercial real estate difficult to digitize are the same characteristics that make it ideal for AI-powered transformation.
DealGround represents this third wave of CRE transformation by creating a single platform where brokers, investors, and analysts can centralize private data, access public property and title records, and query everything through an AI-powered interface. Rather than building another point solution, the platform aims to become what Mosher calls ‘the database of records’ where everything happening with a property – new tenants, lease expirations, rent increases, loan maturity dates – is tracked in one place. ‘Properties are living, breathing organisms. DealGround moves with them over time,’ Mosher notes.
The implications extend beyond mere efficiency gains to fundamentally changing how brokers allocate their time and expertise. ‘The goal is for brokers to spend more time on relationships and less time on administrative legwork,’ Mosher says. ‘Let the system do the research. Let it flag that a lease is expiring in six months, or that a loan is maturing in 2027, so the broker can call that owner with a relevant, well-informed proposition.’ This approach doesn’t seek to replace brokers but rather to enhance their capabilities by automating research and data synthesis tasks, allowing professionals to focus on relationship building and deal making where human interaction remains irreplaceable.
After decades of technological resistance, Mosher believes the conditions for meaningful transformation have finally aligned. The data exists in abundance, AI tools have matured to handle unstructured information, and brokers are increasingly questioning whether their current fragmented workflows represent the best approach. The industry’s shift toward integrated AI platforms could fundamentally alter commercial real estate operations by collapsing multiple systems into unified platforms that provide strategic advantages while preserving the human relationships that have always driven the industry forward.
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