What's Next For AI In Commercial Real Estate

Forbes

08-04-2025

Ryan Masiello, Chief Strategy Officer, VTS.
It's no surprise that AI has emerged as the next frontier in commercial real estate technology, and companies small and large are scrambling to establish their AI strategies to race against the competition.
Proptech providers recognize how crucial the AI boom is and are almost universally developing AI-focused solutions to meet all of the demand and buzz surrounding AI—notably since the launch of ChatGPT, the real fire-starter for the AI conversation across industries. New technology players have emerged as a result, creating AI-based real estate-ready solutions that will change the very fabric of how the industry operates.
This raises the question: Are we in an era of "AI washing"? Many tech providers are claiming they have AI-powered solutions for their customers, but what's credible and what isn't?
According to a January 2025 study published by The Business Research Company, the AI market in real estate is expected to grow from $222.65 billion in 2024 to $303.06 billion in 2025 at a compound annual growth rate of 36.1%. The best, most intentional companies are thinking through how AI can meaningfully solve for pain points their customers are experiencing and drive real value.
The main questions many organizations are asking themselves are how to choose among all of the AI solutions now in the market and how to best implement those solutions into their business to create the necessary efficiencies they were built to provide.
AI has entered the real estate industry in many different forms and has had various impacts, not just on advancements in tech but also on industry trends. As an example, at my company, we've seen how growth in AI has directly impacted office demand. Our most recent quarterly VTS Office Demand Index report noted that San Francisco had seen a 32.4% year-over-year growth in 2024, mainly due to the boom in AI companies.
AI has also impacted other business areas such as asset management and property operations. Most notably, we've seen how it's been incredibly impactful in the various forms of data aggregation and application at scale across a business. This data can be leveraged to uncover the best insights concerning operations, portfolio health and competitive performance.
All that said, a clear data strategy has become necessary for companies to stay ahead of the curve and offers a unique competitive advantage in today's market.
One of the biggest challenges for real estate professionals is sifting through all of the existing AI noise and vetting the right solution when so many more continue to enter the market.
A prime example of a successful AI use case for real estate is predictive analytics. Being able to anticipate market shifts and demand months ahead of time gives a unique competitive advantage to landlords, owners and operators and pushes them to track and analyze market trends proactively. This is virtually a universal value-add for any company in commercial real estate, as staying on top of the market is essential to business operations.
Predictive analytics provides the capability for a company to not just make sense of current market conditions but also get ahead of what's to come, providing a significant competitive advantage. It also forces companies to implement real-time data aggregation; we can't have predictions if we don't have a historical account of market activity.
Predictive analytics are not only incredibly impactful when aggregating key market intelligence but also when landlords, owners and operators look to reevaluate their technology stacks and identify where gaps may be that technology-enabled solutions can fill.
Once you're able to identify the AI solution that will work best for your business, how do you go about implementing it? It's essential to ensure your solution provider of choice offers proper support. Real estate has only just, in the past decade, embraced technology solutions, so there is still plenty to adjust to and learn. AI itself is still being adapted and experimented on, so it will be of greater importance to have those training and support opportunities readily available for team members to take advantage of.
AI is not the be-all, end-all technology solution for every aspect of your business; part of incorporating technology is evaluating what works and what doesn't for your company, and today's market has several solutions. In the future, I expect every solution will have some component of AI within it. Until then, however, the implementation process will still include a trial-and-error period.
This is one of the most exciting periods of technological advancement for the real estate industry, and AI has been the catalyst for this. AI has so many use cases, and while a learning curve will continue (as with all tech advancements in any given industry), I foresee AI having a profound impact on the future of real estate.
I'm very excited for what's to come, and over time, winners and losers will continue to be defined among these solutions—which will only accelerate the growth and sophistication of how real estate professionals operate within their organizations and with their counterparts.
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