AI’s greatest potential in commercial real estate is in freeing up humans to do higher-level tasks and arming them with tools to help them make faster and more informed decisions.Getty Images
Artificial intelligence (AI) is changing the game in the commercial real estate (CRE) space, but for Michael Emory, founder and executive chair of Allied Properties REIT, an owner and developer of urban office space in major cities across Canada, incorporating it wisely means recognizing when it cannot replace human contact.
“We get 40,000 requests for something every quarter from tenants in our buildings,” he says. Where technology has helped us hugely is receiving those requests, establishing time frames with which they are acted upon and providing the wide range of service we need to provide to be a top tier owner and operator of office space.
“But at the end of the day it’s a human being that shows up and addresses either the problem or the opportunity,” Emory says. “The front line for us are the property operators on site, overseeing the buildings 24/7. They are the most important individuals that the people who use our buildings interact with.”
Conversational AI is increasingly transforming core property management workflows by automating tasks that are often repetitive and time-consuming, such as handling inbound leasing inquiries, following up on collections and triaging maintenance requests.
“By automating these repetitive tasks, teams can handle more requests without adding headcount, get information to tenants/prospects faster and reduce errors in routine workflows,” says Stephanie Wood, vice-president at Alate Partners and research lead at Proptech Collective.
One of the most valuable tools is predictive AI, which can be used to identify building maintenance issues, such as through an analysis of HVAC operations, before costly system breakdowns. Machine learning models can be integrated into building management systems to predict high usage times for heating, cooling and lighting, and adjust settings to significantly reduce energy waste and costs. For market analysis and risk assessment, AI models can analyze vast datasets such as demographical shifts and economic indicators, trends in the commercial real estate markets, and tenant feedback and behaviour to forecast property values, rental rates, occupancy levels – all of which can help owners and operators make better decisions on pricing and investments. Some systems can run simulations to model tradeoffs among budget, timelines and regulatory requirements, which can provide early insights into potential risks and efficiencies. And through such things as anomaly detection in surveillance footage, facial recognition and predictive risk assessments, AI can help identify security and safety risks.
AI’s greatest potential perhaps is that it frees up humans to do higher-level tasks and arms them with tools to help them make faster and more informed decisions. For instance, when AI can provide virtual property tours, personalized recommendations and automated communications, that streamlines the work for brokers and agents and frees up more time for one-on-one client interaction.
AI and proptech (property technology) is rapidly changing and, while there is a push in the commercial real estate industry to use it, organizations are approaching it cautiously before scaling too aggressively
“What we’re seeing across CRE is that AI adoption is still largely in the pilot stage or focused on individual use cases and horizontal applications that have baked AI into their platforms,” Wood says.
“Some organizations are seeing real benefits already from specific solutions, but we’re still too early to have a tool that can do everything. We don’t know who will ultimately win in this space. It could be horizontal tools like Microsoft Copilot, established ERPs [enterprise resource planning software] like Yardi, or newer, more modern proptech players.”
The full extent to which AI complements the work of human developers, investors and analysts or replaces it is not yet known. Another challenge is the amount of power required to integrate AI into products, which undermines the sustainability efforts that are a focus in the office, retail, warehouse and apartment sectors.
And accuracy of data, security and oversight are key issues as well. “Data governance and security are consistently the biggest concerns as AI adoption grows,” Wood says. “Real estate firms are definitely aware that mishandling sensitive data could create significant operational and reputational risk, and this is where they’ve been the most cautious.”
Many companies are formalizing governance frameworks, creating AI or data committees, and implementing monitoring and auditing tools to track usage and flag potential issues.
“There’s a strong preference for enterprise or private AI models over public tools to protect proprietary information and, in some places, we’ve seen policies established to ensure human oversight, verification of outputs and controlled access to sensitive datasets,” Wood says.
The quality of the underlying data is critical with AI, and real estate data isn’t as curated, standardized or timely compared with other industries, she says, so that’s been a challenge as well. Tools are available broadly, but return on investment so far is sometimes hard to quantify, slowing down the drive to adoption.
But there’s no arguing that AI is already proving to have benefits with potentially more to come. When it comes to building design and development, AI is helping teams explore and optimize design, cost and permitting decisions, Wood says. While tools aren’t yet fully end-to-end, emerging solutions are experimenting with different elements, such as mechanical, electrical and plumbing planning, as well as material management and evaluating sustainability in building design. AI is starting to support actual design decisions, testing layouts, materials and structural options to find more efficient or cost-effective solutions.
“Building automation is amazing now. It allows you to know what’s going in a restored heritage building in Calgary from our office [in Toronto],” Emory says. “Building controls, air measurements, things like that. I suspect there will be AI technology that will enhance that automation. These are large-scale activities with huge amounts of data – that’s where we expect AI to augment our ability to operate the buildings and serve our customers.”
In the end, AI is certain to continue having a role in commercial real estate and its uses and applications will continue to evolve. The difference maker, Emory says, will be separating the reality from the hype.
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