Cushman & Wakefield builds a foundation for enterprise-wide AI

Cushman & Wakefield has cashed in on several key IT trends over the past few years, positioning the Chicago-based firm well to weather ongoing headwinds in the commercial real estate market stirred by the COVID-19 pandemic.

First there was the company’s full embrace of cloud computing, and then a pivot from project management to a product operating model. And now, with that cloud foundation, Cushman & Wakefield CDIO Salumeh Companieh is putting that product mindset to work to make the most of AI, including a range of generative AI platforms aimed at improving workflow outcomes and productivity.

Working closely with technology partners, the commercial real estate firm has implemented Jasper AI and Microsoft Azure’s OpenAI Service to pump out marketing reports, advisory services, and data insights related to its real estate portfolio, its global clients’ properties, and a range of facilities, leasing, janitorial, and valuation services — all while the commercial real estate market remains in limbo.

“We’re at the bottom of the cycle right now and this isn’t a time where capital is free flowing,” says Companieh, who notes that Cushman & Wakefield’s key advantage to remaining competitive today was its early embrace of the cloud. That early cloud push is providing a strong foundation for the firm’s current foray. “Our strategy is very solid,” she says. “The ideal is to penetrate AI in every piece of our workflow.”

That’s not simply a goal; the firm is doing this today. And the shift to product-based IT has already helped increase its global services revenue from property management, valuation, global occupier services, and a $1 billion janitorial business — the recurring revenues of which have kept the firm aloft while it further aligns its technology strategy to address changes in the market.

Partnering with PwC, Microsoft, and MIT has enabled Cushman & Wakefield “to consume their best-of-breed thinking while we’re building out our own engines,” Companieh says. “About a year and a half ago, we moved to a full product operating model. In prior years, we were project-oriented. By flipping our foundational operating model, using technology has allowed us to be hyper-focused on best outcomes for our clients and colleagues.”

It appears to be working well. In November, the company launched its AI+ services for clients globally and it now has an operational AI hub offshore, the CDIO says. 

The persona approach

Cushman & Wakefield’s strategy to inject AI into every facet of its workflows hinges on its team of 500 dedicated technologists and thousands of contractors, who are working to develop solutions for various “persona” groups within the enterprise, Companieh says.

One such effort involves more than 100 researchers generating market reports and data insights for its global clientele at great capacity using Jasper AI, says the CDIO, adding that more than 250 such generative AI use cases have been identified and tracked within the organization, across multiple personas.

“We got tremendous outcomes through the first 100 pilot group,” Companieh says, pointing to an estimated 30% uptick in market report generation, for example, thanks to generative AI. But the productivity bump has been significantly higher. “The volume of task management reduction in terms of the end-to-end lifecycle has gone from weeks to days,” she says.

Among Cushman & Wakefield’s key personas are marketing and client services. The company’s strategy involves segmenting the lifecycle of its business processes by personas and technology availability. The IT team then takes a “very surgical approach” of ensuring that data types involved in the company’s business processes help achieve best outcomes.

Also vital for success, Companieh says, has been educating and training employees on what generative AI can help them achieve, as well as how best to make use of the technologies at their disposal. It’s also important to start small, she advises.

Cushman & Wakefield’s IT team has also developed and deployed Jasper AI and Azure OpenAI large language models (LLMs) for another key “persona” group: the firm’s advisory team. Through use of these LLMs, the advisory team can extract insights for clients, as well as the firm’s own business units, to help them be more competitive in the market.

Throughout its transformation, the firm has also developed hundreds of applications for property intelligence, client intelligence, and transactional intelligence services that access data from hundreds of data repositories, Companieh says.

AI balancing act

Cushman & Wakefield began its three-year cloud journey in 2016, just as it merged with two other large commercial real estate firms that ran their own data centers.

One of the most important aspects of that merger, which created an $18 billion behemoth, and subsequent cloud transformation was the creation of a universal dataset and blueprint, Companieh says.

The company’s Azure cloud estate and revamped data operations together fuel a sophisticated strategy and change in business model that did not entirely materialize from within. Cushman & Wakefield has relied on its partners to help align its transformed business model with the advanced AI technologies that remain in their infancy. Companieh says she and her extensive team are also working on governance to prevent errors, remain in legal compliance, and deploy AI ethically.

“How do we responsibly generate AI large language models, ensuring the datasets we go after are protected legally and by the spirit of the contract? Once the education and context alignment are equal, then we’re sprinting together as a team,” she says.

That’s only a small example of the benefits Companieh expects from the firm’s massive investment in AI, and she acknowledges it will take much more time and experience with LLMs before she can measure tangible ROI.

“I’m not unlike a lot of CIO peers. We’re in a balancing act,” she says. “I’ve been blessed with the fact that the digital transformation is done so we don’t have a lot of capital going to technical debt and building infrastructure.”