Real estate leaders often start conversations about data with, “I have this cool technology, what can I do with it?”

But a better alternative, Hobbs explains, is to focus first on the challenge first. This sets teams up to correctly find the data that matters most. Here’s the simple problem-insight-data process Hobbs advises:

• Clearly articulate the problem

• Identify the insights needed to solve the problem

• Identify the data required to generate these insights

• Determine the granularity, fidelity, and frequency of the data to trust the insights

This problem-insight-data process allows you to identify the data that matters and solve for that data acquisition in the most cost-effective way.

Without quality data, even sophisticated AI algorithms struggle to deliver reliable and accurate insights.

AI, however, can help create quality data by automating data cleansing and normalization. AI assistants trained on CRE data, processes, and industry terminology become always-available CRE experts, giving real-time responses to queries along with additional, relevant outputs that the requester hadn’t thought to ask.

The potential of AI in CRE is not to replace humans but to augment them. AI eliminates mundane, repetitive tasks, freeing up CRE practitioners to focus on higher-value activities that demand uniquely human skills, like creativity, collaboration, and negotiation.

“Commercial real estate will always be a people and relationship business,” said Hobbs. “AI offers the potential to supercharge those people and relationships. Our motto is ‘Better jobs, not fewer jobs.’”

Watch the full Washington Post Live interview with Robbie Hobbs on the power of data in CRE.