Emerging technologies are changing the relationship between employees and their physical workplaces—a process that has been accelerated by the pandemic and the hybrid/remote work phenomenon.
This naturally has a significant impact on real estate as companies rethink space and how employees will use it in the future. As a result, corporate real estate (CRE) teams must continue to evaluate innovative technologies.
For example, industry experts are turning to artificial intelligence (AI) to benefit from the rising tide of real estate data, so much so that Propmodo recognized several firms—including Skyline AI—for their ability to help the entire industry overcome one of its most pressing challenges.
Considering JLL’s recent acquisition of Skyline AI, it’s worth unpacking why Propmodo was so enthusiastic about the firm’s potential for transforming how companies take advantage of their real estate data.
Technology examine non-traditional data sources to reveal insights
Propmodo highlighted Skyline AI’s unique ability to leverage non-traditional data sources. Skyline AI co-founder and CTO Orl Hiltch provided Risk.net with examples of exactly how data from these sources can be used to approach investment decisions from new angles.
- Using the number of Whole Foods in an area as a likely predictor of affluence
- Analyzing mobile device data to anticipate changes in leasing activity
- Using occupancy algorithms to determine when sellers are aiming to position an asset
Likewise, a recent Globest.com article detailed how Skyline AI helped an investor evaluate a value-add opportunity by flagging data from review sites as indicative of investment opportunities. They then used natural-language processing on the dataset. The end result? The client made a $57 million investment.
AI predicts opportunities faster than industry benchmarks
Most industry benchmarks for property pricing are based on previous transactions, but historical data is often irrelevant in highly volatile markets.
Skyline AI’s technology offers an alternative to the historical approach by predicting more accurate pricing for new investments. By capturing the latest capitalization rate data, the algorithm generates a forecasted selling price.
“We try to predict the discount or premium, in capitalization rate terms, that the buyer and seller would agree upon, given the property’s economic attributes,” said Hiltch. “The value computed with the algorithm will probably be very different from calculating with the most recent historical cap rate.”
What’s next for Skyline AI and JLL?
In a recent letter, the leadership of Skyline AI expressed their thoughts about the recent acquisition by JLL and what that means for the company’s future.
You can also learn more about how JLL plans to incorporate Skyline AI technology into products and services by reading the official announcement.
Need to glean more value from the CRE data you already have? JLL Azara—the first purpose-built CRE data and insights platform—is a great place to start. Contact us for a demo and to learn more about how the platform generates AI-driven insights.