AI Gives Facilities Leaders a Faster Path from Raw Data to Smarter Decisions

A gap is widening between facilities management teams that use data to get ahead and those still managing sprawling operations with spreadsheets. But bridging that divide doesn’t mean a massive, rip-and-replace overhaul. It can start with something as simple as a unified app for connected thermostats, putting every location on a single screen. Adopting new software is a good first step, but the real work is a fundamental change in how work gets done.

Darin Rose, Director of Facilities & Real Estate at the Credit Union of Colorado, brings over 25 years of experience directing facilities and real estate for multi-site organizations in banking, government, and retail. An IFMA Fellow and current member of IFMA's Global Board of Directors, Rose has spent his career turning operational complexity into strategic advantage. That foundation shapes his view of what AI makes possible for facilities leaders: turning raw operational data into the knowledge that drives smarter decisions.

"Data creates information, which then creates knowledge. With AI, you can access that knowledge directly. It provides insights beyond a list of work orders and tells you what actually happened. Were they completed on time? Were there parts issues? That context is the knowledge we can use as wisdom for bigger-picture decisions," says Rose. But to harness AI's potential to transform raw work order data, leaders first have to fix a foundational problem. The industry is stuck in a modern format war, with proprietary systems that can't communicate, and no common standard to unite them.

Just like VHS versus Beta eventually consolidated around dominant formats, the mobile world settled on iOS and Android. A similar evolution is needed for interoperable platforms in facilities, with a common standard like the BACnet protocol for building automation systems to prevent costly data silos.

• Speaking different languages: "If your company uses one building management system and then merges with another that uses two different ones, you're left with three proprietary systems that don't communicate. Having a standardized protocol that allows these platforms to be interoperable is critical," says Rose. For multi-site operators managing acquisitions and mergers, that fragmentation is already a daily reality.

• The sixty-hour slog: The bigger barrier for many leaders isn't the technology. It's the time it takes to get comfortable with it. "The patience required can be a real challenge. I was creating a new website, and a task that should have taken four hours ended up taking sixty because of the learning curve. It's painful to redo work, and it's even worse when you realize you made a simple mistake like forgetting to save," he says.

Closing the gap also requires getting people ready. Success there requires a hybrid approach to training, combining grassroots, peer-to-peer learning with more formalized, self-paced modules. A successful rollout often blends top-down modeling from leaders who transparently share how they use AI with bottom-up initiatives from passionate employees.

• Bottom-up breakthrough: "Change doesn't always have to come from the top. I have a technician who taught himself 3D printing simply because he was passionate about it. He shared what he was learning, which inspired another technician to get involved. Now, they're building upon each other's knowledge," says Rose. That kind of peer-driven momentum, he notes, is often more durable than any mandate from above.

• Trust but verify: Managing AI risk doesn’t require a complex new framework. Instead, Rose advocates for a timeless principle: a dose of healthy skepticism that can make the risk of "hallucinations" more manageable. "The principle has always been 'trust but verify,' and that applies to AI. I asked an AI for basketball game times in Miami, and it gave me a time that seemed perfect. My first reaction was excitement, but I had a gut feeling that something wasn't right. After checking online, I confirmed the game was actually three hours later. It's a good reminder that you still need to validate the information you receive," Rose says.

AI represents an evolution in how we think about professional literacy. For a growing number of professionals, building this new fluency is becoming a necessity, as some corporations are already making it a prerequisite for advancement. The technology is already here, and the central question for many leaders is no longer if they will use AI, but how.

For facilities leaders, this highlights the choice facing them: keep pace with the industry or risk being left behind. "We're at a point just like when the internet first came in. It's open ground to learn, and people have patience for that now. But no one should expect that to be true five or ten years from now. If you don't know how to use the internet today, you're far behind. It will be the same with AI. You won't be able to thrive in your organization, or even in your livelihood without it," Rose concludes.