Real estate is widely considered to be slow in adopting new technologies, she explained, but says “we have hit the tipping point now where the technology is finally catching up with the needs of real estate.”

According to Viriato, commercial real estate involves a lot of steps and many players to pull off a successful project, but many have been effective using old methods to generate strong returns. “The significant investment required to implement new technologies has not been regarded as worthwhile due to the limited evidence that the new way would provide improved performance.”

However, she says that “when we pull apart the commercial real estate business into distinct parts and search for the inefficiencies, there are many complex problems to be solved along the life cycle of a project or deal that can make an enormous impact. With the powerful new systems and tools available using AI we will be able to identify optimal design solutions early in the process, monitor construction sites for errors on the fly, assemble and abstract contracts with ease, give tenants the power to satisfy all their requirements, identify valuation metrics with great precision, and monitor building systems and spaces to ensure the greatest comfort, health, and efficiency.”

While the changes are happening slowly, she tells GlobeSt.com that in the past few years there has been implementation of some of these tools, and as they are refined I expect more widespread adoption to happen quickly.

When asked if artificial intelligence will push the industry forward the way technology has, she says that the industry has been facing one major roadblock on the way to AI adoption in some respects, which is lack of transparency and consistency in data.

Fortunately, she says that there are many machine learning tools (a form of AI) that can help the industry gather larger datasets and more types of data to help us learn about our assets. However, there are limitations, she says, due to the nature of inefficient market dynamics where assets are mis-priced for a broad range of reasons.

“There is also the major roadblock of the proprietary nature of the data owned by each individual investor or firm. Because of the power of AI tools, some could stand to benefit greatly from the insights we get when data is openly available, such as rent data and other deal terms, but there has to be an incentive on all sides if we expect this kind of information to get out there. For the time being, we are seeing innovative approaches to gathering data that technology providers can capitalize on, and there is ample opportunity for more business around the ownership of real estate data, much like consumer data is owned by Google and Facebook; that is, if we let them.”