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Corporate leaders’ often vague predictions about how AI will be implemented are giving way to more fully formed strategies in the commercial real estate industry, recent earnings calls and other communications have shown.
“Now is the moment for a disciplined, evidence-based perspective. [about AI] is most important,” Michelle McKay, CEO of Cushman & Wakefield, said in a webinar on Monday. Impact of AI on real estate.
Below is a snapshot of what leaders at these companies have recently said about how they are bringing technology into facility management and other commercial real estate businesses.
Cushman & Wakefield: Sailing on Stormy Seas
The company recently AI impact barometerThe company calls it a first-of-its-kind research tool that helps occupiers and developers understand the impact of AI across sectors and asset classes. The company says the tool has already given Cushman & Wakefield several negative and positive signals.
“We don’t have all the answers, but we feel there is enough information to sort out current thinking and present some scenarios when making important real estate decisions,” Kevin Thorpe, chief economist at Cushman & Wakefield, said in a webinar on how AI will impact real estate.
Negative signals include a rapid (and rapidly accelerating) decline in employment in white-collar sectors that are more susceptible to automation, and higher vacancy rates in Class B and C offices as automation reduces back-office employment.
“Without a doubt, AI will create winners and losers,” McKay said during his talk. Cushman & Wakefield’s fourth quarter financial results announcement.
Like many other companies in the commercial real estate space, Cushman & Wakefield is focused on implementing technology to improve operational efficiency.
McKay said the company leverages AI in its asset services business to generate insights within its proprietary platform and for space planning in its global occupier services business. The leasing division uses OneAdvise, which helps automate digital tour books, lease negotiations, and benchmarking.
“This actually creates a very powerful data lake that we can use when cross-selling to our clients,” McKay said.
Other use cases include tracking cross-selling opportunities, coordinating employee compensation, managing customer relationships in capital markets businesses, and tracking legal and contractual obligations.
“how [is] Is AI … driving that data and information flow?” McKay said. “When you think about breaking down organizational silos, it’s one thing to do it structurally and organizationally. It’s another thing to let data flow freely throughout the organization.”
CBRE: Digging through data to find treasure
CBRE CEO Bob Salentic said his company is leveraging AI in two areas. One is to increase efficiency and the other is to develop a knowledge advantage to differentiate your products. The first use case involves the deployment of AI that clearly exceeds the economic value of traditional efficiency measures such as offshoring. Sulentic said the company has been disciplined to understand the trade-offs before pursuing efficiency-related AI investments. Fourth quarter financial results announcement.
The second use case involves CBRE’s real estate data, which Sulentic says is the most comprehensive of any company in the industry. He said the company has so far been unable to turn that data into a relatively significant competitive advantage, but it is using AI to change that.
“On balance, we are encouraged by both of these AI-related opportunities with respect to the risks and opportunities facing the market that AI brings to our business,” Salentic said on the earnings call.
He said the company thinks about risk in three broad areas: its trading business, its investment business, which creates or improves physical assets, and its real estate and facilities management business, which manages assets on behalf of its clients.
The company’s trading and investment operations are most protected from disruption by AI, he said. He said the company’s brokerage business is “possible, but not locked into market data,” which means AI can help professionals work smarter through better data insights.
This same dynamic occurs in the firm’s real estate investment business, where clients rely on CBRE to plan and execute complex transactions because of CBRE’s expert creativity, strategic thinking, negotiation skills, deep foundation of market knowledge, and extensive relationships. “None of these are likely to be replaced by AI in the foreseeable future,” Salentic said.
The third part of CBRE’s operations, facilities and asset management operations is likely to be exposed to AI disruption as it eliminates much of the effort required to leverage the large amounts of data being generated, creating both opportunities and risks, Salentic said.
“AI can enable the data and knowledge side of this and remove the intermediaries,” he said. “We believe that the scale and complexity of our customer relationships helps mitigate this risk. It is not easy for AI to disintermediate the labor-intensive aspects with the market-facing aspects.”
Sulentic believes that by the end of 2026, there will be concrete evidence that CBRE has achieved real benefits in extracting the data it holds, absorbing it, and making it available to professionals in an unprecedented way.
“That’s becoming possible with AI, and that’s one of the areas where we’re most encouraged today,” Salentic said. “This saves money in terms of data accumulation and data purchases and increases the efficiency with which data is used by brokers. We are also using the same set of tools to meaningfully reduce the cost of our investigative activities.”
JLL: Peace of mind on rainy days with disciplined data management
A key focus of JLL’s AI strategy is efficiency, CEO Christian Ulbrich said on an earnings call. He said the technology has contributed to strong profit margins over the past two years as the company uses AI to improve productivity across its business areas.
“We were able to drive revenue growth without adding more headcount, which is a clear result of our successful implementation of AI,” Ulbrich said, adding that he expects this trend to continue.
The company has been leveraging AI to identify brokerage opportunities and provide property management teams with “tools to accurately understand current pricing.” [is] “We think about a particular job and how to complete that job in the best way for the client. That applies across the board and applies to our workplace management business,” he said.
To leverage this technology, the company has been investing in disruptive startups over the past decade through its global venture fund, JLL Spark, and is also investing in data platforms, Ulbrich said.
“We have historically been successful in embedding technology and building unique datasets across our core services,” he said in the JLL article. Fourth quarter financial results announcement.
“We’ve spent a lot of money organizing data, which is no small feat in an organization that’s been built country by country over such a long period of time. But we’re solving that problem and really helping our clients in a meaningful way by providing insights that aren’t easily available to people who don’t have that data,” Ulbrich said.
He added that the company continues to invest in its proprietary platform and develop new internal tools that its teams can use to better serve customers. For the time being, JLL “does not intend to increase its investments in third-party proptech startups,” he said.
“Data is so important that it needs to be done in-house,” JLL Chief Technology Officer Yao Molin told Facilities Dive in a 2024 Q&A interview. “A lot of traditional commercial real estate companies develop technology in an outsourcing model. We want to build and manage the data. We want to protect the data. We want to make sure we build our own secret sauce so that we can stand out from a brokerage standpoint and from a facility management standpoint. And our competitors can’t just copy it or license it.” [our approach]”
Ulbrich echoed similar sentiments during JLL’s earnings call, emphasizing that the company has vast amounts of proprietary data that is difficult for other companies to collect. “Using that unique data, we can build tools that enable our employees to drive better outcomes for our clients, which will lead to increased revenue per capita, not just for our dealmakers, but for other areas of our business,” he said. “The bigger your business, the more protected it is because the data is there.”
At the same time, investments in data platforms and AI are intended to give professionals the tools to deliver more value to their customers, not replace what they are doing.
“The complexity of the commercial real estate asset class, the importance of real-time local market expertise, and the associated fiduciary responsibilities create structural barriers. [to disintermediating professionals]“AI is moving very fast, but ultimately it will require human interaction, and that human interaction will be performed by people who have the right data at hand and the knowledge to provide that service.”
