AI is everywhere right now, including in commercial real estate. But for most property and facilities teams, the conversation often feels abstract.

What does AI actually do in day-to-day building operations?
And more importantly, how does it help teams work more efficiently?

The reality is that AI in CRE isn’t about replacing people. It’s about improving business processes, supporting daily work, and helping property teams operate more efficiently while still centering relationships and the personal experience.

The real challenge: too much fragmentation

Before AI can add value, there’s a more fundamental problem most teams face: fragmented operations.

Property teams are often working across:

• Multiple systems for work orders, inspections, and vendors
• Disconnected data sources
• Manual reporting processes
• Limited visibility into what’s actually happening across properties

This fragmentation makes even simple tasks harder than they should be.

And it’s exactly what limits the effectiveness of AI. As Sharon Hunt, Vice President of Product Management at JLL, notes, the challenge is not just whether teams are interested in AI, but whether they can translate that innovation into everyday operational impact.

What AI actually does in building operations

At its core, AI helps teams make better use of the data they already have.

Instead of digging through systems or compiling reports manually, AI can:

• Surface insights across work orders, vendors, and operations
• Identify patterns in issues, delays, or recurring problems
• Help prioritize tasks based on urgency or impact
• Reduce time spent searching for information

The goal is not to replace human decision-making, but to work in tandem with it by reducing friction, surfacing insights, and making day-to-day workflows easier to manage.

AI is most effective when it is embedded directly into workflows rather than treated as a standalone tool. The goal is not to introduce new complexity, but to make existing workflows easier, faster, and more visible, allowing teams to focus on outcomes rather than process management.

In practice, this means AI is not something teams actively “use” in isolation. It becomes part of how work gets done, quietly improving how information is surfaced, decisions are made, and tasks are prioritized across daily operations.

Why data structure matters more than AI itself

One of the biggest misconceptions about AI is that it works independently of your systems.

In reality, AI is only as effective as the data behind it.

If data is:

• Disconnected
• Inconsistent
• Spread across multiple tools

Then AI has limited ability to provide meaningful insights.

This is why centralized platforms and unified operations matter. They create the foundation that allows AI to actually deliver value.

Moving from automation to intelligence

Many CRE teams are already using automation in some form. But automation alone only solves part of the problem.

Automation helps execute tasks.

AI helps understand them.

For example:

• Automation can assign work orders
• AI can identify why certain issues keep recurring

That shift from execution to insight is where real operational improvement happens.

What this means for CRE teams

AI isn’t something teams need to adopt all at once. A more practical path is to start small, identify where AI can make the biggest impact, and build from there.

As Hunt outlines, a useful framework is “Crawl. Walk. Run.” At the crawl stage, teams identify repetitive workflows, large datasets, and coordination-heavy processes where AI can help. At the walk stage, they integrate AI more deeply into everyday work and begin measuring response times, costs, and tenant satisfaction. At the run stage, they scale those insights across the portfolio to improve efficiency, sustainability, and tenant experience.

For CRE teams, the takeaway is simple: the teams that benefit most from AI are the ones that first centralize workflows, improve visibility, and create a stronger operational foundation.

Final takeaway

AI in commercial property management isn’t about hype. It’s about making everyday operations easier to manage.

When workflows are connected and data is centralized, AI can help teams reduce manual work, improve decision-making, and gain better visibility into operations. But the bigger opportunity is not simply adopting more technology. It is identifying the right use cases, introducing AI thoughtfully, and measuring its impact over time.

AI works best when it solves real operational problems. See how CRE teams are using smarter building operations technology to reduce friction, improve visibility and drive better portfolio performance.