Nick Romito, CEO of VTS.
Commercial real estate has seen a number of seismic events that have altered the strategy and operations of companies. This includes the global financial crisis, Covid-19 (which accelerated the rise of remote work) and the overall crushing of interest rates.
These moments proved pivotal in helping place companies squarely within one of two camps: those that leaned into change and learned to adapt versus those that resisted and were left behind.
Today, I see ourselves in the midst of another altering event: the acceleration and implementation of AI. The question every landlord, investor, property manager and broker needs to ask is, which camp will you and your company land in?
Why This Matters For Commercial Real Estate
For decades, CRE has been powered by people, paper and painstakingly manual workflows: proposals re-keyed, market comps hunted down and asset reports assembled by hand. That’s the pre-AI way of operating: slow, fragmented processes that are dependent on armies of analysts to process information.
Companies that have embraced AI and embedded it in their strategies and processes see things differently. They’re using generative AI to extract data directly from proposals, run comps, auto-generate copy in leases and surface insights across their portfolio and the market.
Real-World Applications Of AI In CRE Operations
According to Summer 2025 data from Morgan Stanley, approximately 37% of processes in CRE can be automated by AI, saving the industry a collective $34 billion.
Today, there are numerous ways to apply AI to your day-to-day operations to increase efficiency and give your employees time back to increase revenue.
Based on my years of experience as a broker and then as CEO of a commercial real estate platform, I hear customers’ pain points across the industry. In this time, these are some of the most meaningful applications I have found for AI to deliver the most value for CRE professionals:
• Predictive Data: AI can forecast future property values, rent growth and market desirability using time-series and machine learning models. When paired with insights from leaders in the industry, it can deliver answers to many questions professionals have about performance in the market and assist with investing, budgeting and more.
• Proposal Assistance: Leasing and asset teams can automate proposal entry by leveraging existing documentation, as well as model deals by providing cash flows and budget comparisons. This removes the need for manual entry in transactions and helps ensure a greater degree of data cleanliness and accuracy. Like with other uses of AI, this helps give time back to leasing and asset teams.
• Property Management: Tenants as well as property managers can benefit from automated service requests, which I find easier to make and to attend to. Maintenance submission orders can be made via voice or text through chatbots or virtual assistants, serving as the first line of defense for staff and ensuring faster delivery of work orders to spaces.
• Co-Pilots: Assistants that embed within your workflows can help with decision making, automate and manage repetitive tasks and connect fragmented tools. These co-pilots essentially serve as research assistants, deal assistants, maintenance partners and tenant concierges.
Risks To Watch
However, commercial real estate, like many other industries, has seen tech providers rush to tout features or products as AI-enabled, while in reality, they are simply slapping an AI label on existing tools.
Because of this, when vetting AI tools, it is important to consider the value the provider can credibly provide your company, as well as what benefits successfully implementing said solution(s) will do for your teams and revenue. Due diligence is key, and consideration must be given to which tasks and processes can reasonably be automated or simplified.
I think one of the biggest concerns when examining AI solutions should be the rate of adoption; I find this to be the biggest key to, or detractor from, success. Because of this, it’s critical that key stakeholders and intended end users buy into the technology’s value and see the potential it can provide. This helps guarantee that the tools are used as intended and that true value is delivered.
Ultimately, choosing the right AI solution involves considering what pain points can be solved with said technology at your company, and how much more bandwidth employees will have to focus on other tasks to increase revenue. No matter how helpful the potential use cases for these tools are, without intentional planning, your time savings from AI can easily be lost to administrative drift or uncoordinated work.
Where The Industry Stands Today
Capital markets are already demanding higher efficiency; as a result, investors are beginning to gravitate toward landlords who can demonstrate an AI-driven margin expansion.
Tenants, as well, are beginning to expect a quicker and more frictionless experience when signing deals and communicating with management. For the same reason, brokers and analysts are choosing firms where technology helps ease their day-to-day tasks and allows them to move with greater speed.
We’re seeing some of the industry’s largest owners, operators, property managers and brokers embracing AI as an integral part of their strategy and operations. They’ve shifted from pilots to platform strategies, from experiments to execution.
Failing to embrace AI isn’t just inefficient; it can also be a competitive liability. Those firms that have an AI strategy they are actively implementing it can move faster and with greater agility, while also leveraging the best information possible.
AI has already begun to reinvent how real estate is marketed, leased, managed and invested. The line is drawn. Which side will you land on?
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