How a real estate management firm became a data-driven AI company

Jones Lang LaSalle (JLL) may not be a brand you hear about every day, but the real estate management firm’s roots stretch back more than 200 years. Today, JLL employs 112,000 people across more than 80 countries and reported annual revenue of over $23 billion last year.

In 2019, long before most people had ever heard of a large language model, JLL made a conscious commitment to become a data-driven technology company and JLL Technologies (JLLT), the company’s technology arm, was born. As AI surged in subsequent years, that choice looked particularly smart.

In one of its earliest moves, JLLT hired Yao Morin as chief data officer to run their burgeoning data and analytics operation. She had previously been at StubHub and prior to that, Intuit, where she witnessed how fintech had transformed banking over the years. Morin saw JLL at the very start of a similar journey, using technology to transform commercial real estate by leveraging data, a prospect she found extremely intriguing. “It was a very exciting area of problems for me to solve,” Morin told FastForward.

The goal was to move beyond simply using technology to manage the nuts and bolts of real estate investments, but to take advantage of the underlying data to drive insights and help customers make better, more informed decisions about their properties. It would also eventually play a role internally to help improve company operations. To get there, JLLT began recruiting tech talent from across Silicon Valley and elsewhere to build a broad, skilled and knowledgeable technology team. 

That initial push to build an experienced team paid off. Today, Morin is the CTO in charge of executing the company’s technology strategy. Meanwhile JLLT has grown from humble beginnings in 2019 to a booming operation with over 3300 technology-focused employees and a $400 million annual budget.

Putting data first

Having quality data is essential to any AI strategy, and Morin wanted to bring a data-first mentality we see at big financial institutions like Capital One to JLL. That kind of mindset starts at the top. “A lot of companies say that technology and data are important to them, but our CEO continues to emphasize how they are really an integrated part of our services,” she said.

When Morin came onboard, data was spread out in a disorganized way across the company. She said where many companies fail when it comes to data is not taking a long view. It takes time, a significant investment and most importantly, patience, something many organizations lose along the way. “If we truly wanted to leverage data, then we really needed to have the data organized and curated, while building a foundation to fuel that technology growth,” she said. 

If we truly wanted to leverage data, then we really needed to have the data organized and curated, while building a foundation to fuel that technology growth.

From the start, Morin went to work building that foundation. “That work is really paying off today by allowing us to build technology at scale, while also using our data in a scalable way to provide the insight that our clients need,” she said. 

Putting AI to work

Getting its data house in order had a number of long-term benefits. It gives customers access to information about their properties they might not have been able to surface before, and enables business units to tap into the data they need, exactly when they need it. What’s more, in the age of generative AI and AI agents, organizing your data sets you up to build stronger models tailored to your business.

In fact, JLLT’s AI approach starts with JLL Falcon, the company’s in-house AI platform that combines the company’s proprietary data with AI models to help Morin’s team build custom AI applications for clients and employees alike. 

One such application is JLL GPT, the company’s AI assistant, released in 2023 with the goal of helping answer employee questions. Just over two years later, the bot boasts 27,000 weekly active users, a tremendous success story in Morin’s view. More recently, the company released Prism AI, an add-on to their Prism property management platform, designed to help customers automate and speed up building management tasks. 

What to build, what to buy

But no company can do everything themselves, even one as tech-focused as JLL. They follow a four-part approach: build, license, acquire and invest. They build any elements they think are core to the business, leverage their underlying data and give them a competitive edge.

“For example, we do our enterprise data platform and our AI platform ourselves because we need to guard that secret sauce on how we organize our data, curate our data and build our AI applications,” she said. That means they are almost always going to license operational tools like CRM, ERP or financial software, which aren’t central to the business.

They tend to buy adjacent businesses that solve specific problems for the company. For example, they acquired the cloud lease management platform Raise Commercial Real Estate in October 2024. Alongside acquisitions, the company invests in promising proptech startups through their corporate venture capital arm, JLL Spark, while also working with other up-and-coming companies.

“We work with startups both inside and outside our portfolio. In terms of the startups that are within our portfolio, our corporate venture fund is a very important element of our technology strategy,” she said.

Morin says all of these elements form the core of the JLL Technology strategy. That includes a data foundation that has set them up to take advantage of AI or whatever tech happens to come along. But she says it’s never just about technology. It’s about putting it to work.

“One of the learnings that we have in this five-and-a-half-year journey is that technology is never useful on its own. It's about how people use it and how many people adopt it,” she said. 

Featured image courtesy of JLL.