There’s a quote often attributed to Henry Ford about the advent of cars: “If I had asked people what they wanted, they would have said faster horses.”

Whether or not he said those words, the same concept can be applied to how many commercial real estate businesses are approaching artificial intelligence, said Justin Lischak Earley, head of real estate innovation at Orbital, which provides real estate AI solutions for lawyers and professionals. 

According to Earley, there’s too much focus on processes, not outcomes. 

“They ask: How do I take this process and turn it into something that a machine automates?” he said. “But this won’t produce AI solutions that transform transactions. Rather, we should focus on what results we’re seeking and the right tool to get us there.”

Bisnow spoke to Earley about CRE professionals’ misplaced focus on deploying AI and how they need to rethink their strategies. 


Bisnow: What is wrong with how CRE is approaching AI right now?

Earley: Throughout the last few years, the approach in real estate has been ‘give everyone AI and magic will happen’. This isn’t reasonable. 

If you handed someone a car in 1900 and said, ‘Now transportation will happen,’ it wouldn’t have worked. You need roads, traffic laws, fuel stations. 

The mere presence of this fantastic new technology doesn’t get you there. It takes time for things to develop around it for things to come to pass. 


Bisnow: What does the AI ecosystem look like for real estate?

Earley: It’s about building tools that are fit for purpose, not just fit for use. To stick with the car analogy, I’ve got a hatchback, and if I wanted to haul timber, I could do it. So it’s fit for use. But the boards would stick out; it’ll be awkward. I’m not going to get nearly as much value out of it as if I used a pickup truck, which is fit for purpose.

There are many AI tools you can use in real estate, but that doesn’t mean they are fit for purpose. As the ecosystem matures, we’ll see more tools specifically developed for the sector. 

Orbital’s products are built by people who have significant experience in CRE, bringing together over 250 years of combined real estate legal expertise. This collective expertise is built into our solutions, and we have a singular vision on serving this industry. 


Bisnow: What could AI achieve if it were deployed properly? 

Earley: There’s the old phrase from a mechanic: ‘I can do it fast, I can do it cheap, or I can do it right. Pick two out of those three.’

Properly built, properly deployed, fit-for-purpose AI can break that triangle at last. As these systems develop and we advance in both technology and people’s willingness to use it, we will see CRE transactions happen faster, cheaper and ultimately better with less risk involved.


Bisnow: Will this ultimately result in fewer jobs?

Earley: There are two theories on this. One is that AI could be problematic for people newly entering a profession because a lot of that repetitive rote work that previously would have been a training ground may be taken by AI. 

Another school of thought is that there’s a lot of work that doesn’t get done because we’re out of time and capacity. Deploying free time efficiently could de-risk transactions and help break the triangle. 

We don't know which way the future will develop, and it will probably be on a firm-by-firm basis, but my belief is that one way or another, AI is going to come into the sector. 

A junior person won’t have to do a lot of unfulfilling, file-sorting work and instead upskill faster. The more you have access to fit-for-purpose AI tools, the more you can improve at using them for their purpose. 


Bisnow: How can the industry get the most out of the new AI solutions as they become available?

Earley: AI runs on data. What I find is that people only think about outcome data or decision data. If you want to truly train a system correctly, you need to track not only the decision that was made but the resulting outcome.

The trouble with real estate is that the time difference between the two can be long. The average hold period of a CRE asset is seven, maybe 10 years. So you have to be a long-term thinker in real estate AI.

The other challenge is that data is scattered. There are so many people involved in a CRE transaction and no centralized collection of data. 

This gets back to the importance of expertise in this space. You can’t be a domain tourist in CRE, someone who lacks visibility across the sector, and expect to get results. The industry is complex, especially in the U.S., where each jurisdiction has different laws and practices, and each transaction has different buyer and lender profiles.

You have to know how to deploy tools and where to look for data that can build something fit for purpose. The more you encode knowledge into an AI product, the more predictable you can make that product’s work and decisions. 

Then, you don’t need to wait the seven years that it takes to get data but use a tool that does the job you need it to.

This article was produced in collaboration between Orbital and Studio B. Bisnow news staff was not involved in the production of this content.

Studio B is Bisnow’s in-house content and design studio. To learn more about how Studio B can help your team, reach out to studio@bisnow.com.