“If you are not adopting AI today, you’re going to be made obsolete. Your career is at risk, your company’s at risk.” This stark ultimatum, delivered by Fundrise Co-founder and CEO Ben Miller, cuts through the typical technological hype cycle, framing the current wave of artificial intelligence not as a luxury, but as an existential imperative, particularly for industries historically slow to embrace digital transformation. For Miller, who has spent the last decade building a platform dedicated to the democratization of private market investing, AI is the ultimate tool for tearing down the old guard and leveling the playing field.
Miller recently spoke with CNBC Senior Real Estate Correspondent Diana Olick on Property Play, detailing Fundrise’s journey from real estate crowdfunding pioneer to a sophisticated investment manager now wielding domain-specific artificial intelligence. Fundrise, which manages over $3.5 billion in assets and caters to two million individual investors, initially gained traction by breaking down the barriers to entry for commercial real estate (CRE) investments, famously allowing investments as low as $100—a minimum later dropped to $10. Their initial mission was simple: bypass the traditional institutional gatekeepers and offer retail investors access to assets previously reserved for the ultra-wealthy.
Miller’s drive, as he explained, stems from a formative skepticism toward the established financial system following the 2008 crisis. “My dream is to get wealthy by tearing down the incumbents. And so technology is the best way to disrupt the status quo,” he stated, outlining a philosophy that has guided Fundrise’s evolution. After successfully proving the model for real estate—forcing legacy institutions to “retailize” their offerings—Fundrise pivoted to democratize access to private technology equity, investing in high-growth companies like OpenAI, Databricks, and Anthropic through non-traded public venture funds. This progression underscores a belief that technological disruption is the only constant, and staying ahead means continuously finding the next hill to climb.
That next hill is RealAI, Fundrise’s proprietary AI platform designed to function as a real estate analyst available to everyone. Miller argues that while generalized large language models (LLMs) like ChatGPT are impressive, they lack the real-time, domain-specific data required for accurate, high-stakes financial analysis. RealAI is designed to address this deficiency by integrating vast, granular data sets specific to the CRE and residential markets.
The platform’s analytical power hinges on its proprietary data infrastructure. Miller revealed that RealAI is built on a database of "three and a half trillion data points of all the real estate knowledge you would want... down to the city block." This includes detailed information on every property in America, coupled with "people data" tracking demographic movements, income levels, and even consumer behavior. This depth of information allows the platform to perform granular tasks like rental comparison analysis, property manager assessments, and scenario planning—capabilities traditionally confined to large institutional firms with dedicated machine learning teams. For instance, RealAI can analyze a specific apartment building and determine if its rents are "under market" by cross-referencing rental prices with the actual median income and wealth metrics of the tenants living there and in surrounding blocks. This fusion of public records, market data, and proprietary consumer intelligence creates an information asymmetry that Fundrise is now packaging for the masses.
The competitive implication of RealAI is profound. Miller emphasized that Fundrise is leveraging this technology to eliminate the need for dozens of human analysts, drastically accelerating due diligence and reducing transactional costs. This efficiency gain is not just a cost-saver; it fundamentally changes the speed of investment. One of Fundrise’s beta customers noted that the platform’s analytical capabilities meant they would likely hire half the number of real estate analysts they had planned. Miller confirmed this trend within Fundrise itself: since rolling out internal AI tools, they have not needed to hire new personnel for customer service, financial analysis, or product development roles.
This impact extends far beyond Fundrise’s internal operations, pointing to a broader macroeconomic shift (Insight 3). Miller posited that AI’s ability to displace "cognitive labor" will act as a massive deflationary force, depressing wages in middle and back-office roles—a trend already observed across various industries. This deflationary pressure, he argued, will inevitably lead to central banks lowering interest rates. "That shock to interest rates combined with I think Trump’s desire to lower interest rates... the real estate industry will rip," Miller predicted. This environment will favor assets that are already insulated from economic volatility, such as high-end residential, high-end retail, and data centers—the physical infrastructure underpinning the AI revolution itself.
Miller concluded that while technology is creating income inequality and disrupting traditional career paths—a trend he finds unfortunate—the response cannot be to ignore the innovation. Instead, the focus must be on democratizing access to the tools and data that drive success. RealAI serves as a co-pilot, amplifying the abilities of those who adopt it, transforming everyday investors into data scientists who can leverage institutional-grade intelligence without needing a specialized degree or millions in seed capital. Fundrise’s mission remains disruption, ensuring that the benefits of this technological tsunami are not monopolized by the largest institutions but are distributed to the individual investor.
