4 ways AI helps CRE investors combat industry inertia

Despite interest rates stabilizing and inflation dropping from 2022 peaks, real estate investors are still in choppy waters. Private investors have to put bigger cash deposits to secure their properties, while institutional investors have to pay more for the debt they use to play in the market. Meanwhile, occupancy is stubbornly low—which continues to have ominous implications for the long-term value of dwindling city centers. There is also ongoing pressure to shift to a more involved business model where landlords provide amenity services to the tenant, sharing the operational costs.

The meteoric rise of generative AI has raised many questions about how it may impact, if at all, the real estate investment market’s woes. In our recently published white paper, Breaking ground: How CRE investors are embracing AI for real results, we outline four key ways AI (both generative and older forms of analytical models) can help combat the inertia in this market. Below is a shortened summary of the key opportunities.

For example, Landsec says they have already deployed AI methods in some of their back-of-house processes, reducing process time by 75 percent. One way they are doing this is by improving their building management systems (BMS) operations, trialing predictive and AI-driven technology to optimize heating, ventilation and air conditioning systems. This can support ESG reporting on the portfolio.

One area ripe for reworking is the abstraction, summarization and tracking of changes to lease documents. As these documents are often very large, this can be a huge time saver. For instance, leasing teams at JLL are using APIs to extract numeric values from different clauses in their client invoices. Collectively this is saving hours of time for these employees, which can instead be spent on more complex tasks.

For instance, JLL’s Building Engines’ Prism software solution recently announced that it can integrate with Jones to optimize the certificates of insurance (COI), minimizing the need for landlords, tenants, and vendors to send countless e-mails in their efforts to verify compliance. Building Engines’ Prism solution uses generative AI to automate the document verification process, validating that the correct language is used to reflect the certificate’s compliance rules.

Orbital Witness, invested in by JLL Spark, helps teams in the legal and property sectors to store all the data related to a due diligence for a property acquisition in one place. The solution enables them to locate and order information in a highly structured manner. And by training its data model using generative AI to recognize keywords and notions in the documents it reviews, it can search them more efficiently than a human equivalent and use the insights to generate a range of report templates for communicating this information to the relevant stakeholders.

Combining a good understanding of market opportunities with a targeted use of AI for internal innovation is a winning formula in today’s challenging market. Even with its current issues, the real estate investment market can be a promising prospect. According to JLL’s Global Capital Outlook, private real estate investments have recently been less volatile than many other investing options, delivering solid returns. From 2013 to 2023, the returns for US private real estate were 6.36%—outperforming hedge funds, corporate bonds, and stocks in emerging markets. There are also noteworthy growth segments: grocery-anchored retail centers, medical offices and industrial properties.