Few CRE companies have achieved their AI goals. This is why

A version of this article first appeared in the CNBC Property Play newsletter with Diana Olek. Property Play covers new and evolving opportunities for the real estate investor, from individuals to venture capitalists, private equity funds, family offices, institutional investors and large public companies. subscription To receive future issues, directly to your inbox.

The commercial real estate market has historically been slow to modernize, yet it appears to be accelerating the adoption of artificial intelligence.

Companies are moving beyond initial testing and exploration to more targeted applications aimed at redefining value, according to a new JLL study.

The survey of more than 1,500 senior investors and decision-makers across industries found that, although still in the early stages, organizations are making AI a priority in their technology budgets. They are also moving from using it solely for efficiency to focusing on how to grow their business.

JLL found that 88% of investors, landlords and landlords said they had begun experimenting with AI, with most looking to implement an average of five use cases simultaneously. According to the report, more than 90% of property occupiers are running AI pilot programs in the real estate sector. Compare that with just 5% of AI pilots who started two years ago. Adoption happens quickly, but it’s not exactly easy.

Only 5% of participants said they achieved all of their program goals, while nearly half said they achieved two or three goals. Many efforts are still experimental, without much growth.

“If you think about commercial real estate, they usually don’t adopt technology quickly, and they’re usually skeptical,” said Yao Muren, chief technology officer at JLL. “So the high number of adoptions is actually a big surprise to me. What’s not surprising on the other hand is that only 5% think they’ve met all the goals. That’s pretty much in line with a lot of other industries as well.”

The reason they did not achieve their goals was because the goal line moved. Companies have gone beyond simply wanting to do certain tasks faster, or so-called operational efficiencies. They are now linking AI to their revenue goals.

For example, some use it to help them improve their investment risk models, and make investment and portfolio decisions based on AI outputs. This will require major changes in the fundamental way you operate.

“When you really start moving toward the revenue side, the margin expansion side, it’s going to take a lot more than just using technology,” Morin explained. “You can’t just say, ‘Okay, I’ll save you 10% for doing this exact thing.’ Companies need to really rethink their operating model, rethink how they’re structured to actually realize the savings.”

So companies are investing heavily in AI, despite the economic headwinds. More than half of the investors surveyed by JLL have achieved significant balance sheet growth over the past two years in this area. Their top spending is on strategic consulting on technology or AI, and most indicate that their budgets have increased only because of AI. The spending then goes to upgrading both cybersecurity and data security measures and the infrastructure needed for AI integration.

What I found really surprising, Maureen said, is that although most companies think companies will start using AI for simple, low-risk, or low-hanging fruit tasks, that’s not the case at all.

“Our survey showed the opposite. We have reached a point of evolution, beyond this initial stage of skepticism, where companies are truly focusing on competitive advantage for pressing business problems, using AI to solve them rather than [just] These are simple, low-risk operations.”