Artificial Intelligence—More Than Just Data-Gathering
Much has been written and spoken concerning artificial intelligence and how it benefits commercial real estate. AI is used for everything from portfolio analysis to documentation to automating repetitive tasks. However, Jules Barker, associate partner with McKinsey & Co., indicated that there’s more to AI than feeding or gathering data in a recent Q&A with McKinsey Executive Editor Katy McLaughlin.
The First Steps
Initially, AI users need to ask about the first steps. “They need to step back and ask, ‘What are we struggling with? What’s our competitive advantage, or what should it be’?” Barker said. Following that is an understanding of the process and talent challenges posed. “They need to think through what data and system they need and who can help deliver it,” Barker explained.
As a follow-up, McLaughlin asked how real estate companies could determine what problems to tackle. Barker suggested that company teams should analyze their challenges and what opportunities can be captured with artificial intelligence. “The senior leadership can prioritize projects based on estimates of how long each one will take, the ease of implementation and the potential for impact,” Barker said.
Then and Now
Barker also outlined data that buildings collect today that wasn’t available five years ago. He said that in the past, office environment data was somewhat elusive. “It was pretty expensive to do anything more than count the number of people swiping into the office every day,” he said. Data concerning space usage is now available thanks to footfall counters, passive infrared sensors, Bluetooth beacons and Wi-Fi systems.
Additionally, all of that data can be gathered in one place. “Granular data can be layered with, say, historical property performance data and local and regional demographic data to create a comprehensive view,” Barker said.
Examples he offered included:
- An investor who needs to know what’s required to bring a building up to sustainability standards. “They can bid on it faster, or bid more for it, and capture an advantage by doing so,” Barker commented.
- A mall operator interested in demographics and detailed footfall throughout the property. “The operator can more accurately target the best possible tenant for a particular retail outlet,” Barker added.
Additional Takeaways
Barker suggested that companies using AI can identify quick wins and high-priority transformative use cases. This process leads to “no-regret actions that rapidly yield results,” which, in turn, “can demonstrate the momentum to stakeholders who might otherwise be blockers to change,” he said.
Additionally, AI implementation and usage isn’t one-and-done. “Any tech build requires continual design and scoping choices that cumulatively shape the end project,” Barker said.
