JLL AI Leader Says Data Debt Is Undercutting AI Returns In Commercial Real Estate

While a recent JLL survey finds that 88 percent of commercial real estate (CRE) investors are now experimenting with AI, only 5 percent are seeing real returns, constrained by immature data foundations, a lack of technical talent, and the technology’s still-nascent state. CRE has spent decades accumulating data debt in the form of fragmented departmental datasets, mismatched property identifiers, and the absence of firm-wide platforms or governance to tie everything together. These gaps are driving the divide between AI investment and impact, making it more difficult to achieve the very AI use cases investors care most about, from sharper investment decisions to stronger portfolio risk monitoring and clearer market opportunity discovery.

Geoff Kau is a technology and strategy executive with deep experience at the intersection of data and real estate. As the Head of AI and Corporate Functions Technology at JLL, he brings a clear view of how the industry’s digital transformation is unfolding on the ground. Before joining JLL, Kau held senior leadership roles at Ping An and served as an Engagement Manager at McKinsey & Company. His perspective makes one point unmistakable.

"The top AI use cases require huge amounts of very high-quality data, but the commercial real estate industry has historically struggled to capture, clean, and make use of data at scale," said Kau. The industry’s weak foundation has created a clear sense of urgency. Spurred by a fear of being left behind, over 90 percent of companies are experimenting with generative AI, drawn to the massive bottom-line potential of optimizing portfolios and automating operations.

• Playing catch-up: The industry’s rush into AI reflects less excitement and more pressure, as firms try to compensate for years of underinvestment in data and technology. Leaders see competitors moving fast and feel the cost of falling further behind. "You can very clearly see that there's a FOMO mentality going on. Commercial real estate as an industry is usually not a front runner or a leader in any type of tech, so when you see 90% of companies doing something, there's a mentality of being left behind and losing competitive edges," Kau explained.

• Dual appeal: A major reason CRE has rallied around AI is that the technology aligns directly with the industry’s two core levers: automating labor-heavy processes and strengthening data-driven decision-making. Routine administrative work across buildings and portfolios creates enormous potential for automation, while advisory and capital markets teams depend on analytics that AI can significantly elevate. "Commercial real estate is very labor-intensive, with a lot of routine admin tasks, and AI has huge potential there. On the other side, it's around decision-making and data analytics, and AI is also very good at that."

To get any real value from AI, many firms must first do the unglamorous but vital work of modernizing their data infrastructure. Kau stressed that this is a challenging, multi-year journey that requires major investment in a corporate-level data strategy and the development of an enterprise data platform to aggregate siloed information.

• Finding the jewels: But modernizing CRE data isn't just about aggregation, explained Kau. It requires governance, consistent identifiers, and a clear understanding of which information actually drives value. "You need to identify what fields are required and critical. We call those the crown jewels, because there are some data dimensions that are more valuable than others."

• Calling for backup: The industry’s data challenges are magnified by a significant talent shortage, with half of CRE firms reporting no technical expertise beyond basic IT support. Kau noted that companies are starting to address the gap. "A positive sign is that a top priority for almost half of companies is engaging outside help to plan their tech, AI, and data strategy for the future," he said.

Instead of leveling the playing field, AI is giving the industry’s existing technology leaders an even bigger lead. Kau noted that one of the most insightful findings from the JLL survey is that companies with a history of successful tech programs are the ones pulling ahead in the AI race. "The idea that AI will enable laggards to leapfrog the competition is not what we're seeing," he said. "The leaders who have had successful tech programs are still leading in AI, and the rest are still lagging. What has made a company successful at tech still holds true and is propelling the leaders further ahead."