Leveraging AI in Property Management
Back to Blog

Leveraging AI in Commercial and Multifamily Real Estate

Posted on December 11, 2023 by Andrew J. Nelson

Professional business woman employee working on computer in office.

A new generation of technology is coming to property management. Building engineers have increasingly implemented smart building technology to improve energy efficiency and sustainability. Now, the application of artificial intelligence (AI) stands to greatly enhance those efforts — and extend the technology to other aspects of property operations.

The timing is opportune. As we summarized in this e-book, property market conditions are expected to be more challenging in the coming years, according to a leading commercial real estate (CRE) industry report. With less favorable financial market conditions, CRE investors will need to focus more on property operations to generate returns.

The Next Generation of Smart Building Systems 

Computerized building systems have existed for decades in various forms, but intelligent building technology only became feasible in the last 20 years with the greater availability of broadband internet and the emergence of the Internet of Things (IoT). Now, IoT allows building system components to be connected online, making it easier to compile and analyze system operation data and ultimately optimize performance. 

AI is making that possible in several ways. One promising area is predictive maintenance — using AI to mine building system data to predict potential problems. Companies are using AI-enabled analytics to predict which building components might fail. With this knowledge, building engineers can avert emergencies by scheduling preventive maintenance before the system component breaks. This approach not only reduces downtime but also saves money.

Soaring energy costs and rising stakeholder demands to expand corporate sustainability efforts create a greater urgency to adopt even smarter building systems. AI can enable companies to meet this demand with energy optimization initiatives. Energy management systems (EMS) are getting smarter and better, using machine learning to analyze HVAC, lighting, and other energy systems data to identify and implement energy-saving measures. Specifically, AI can incorporate weather predictions to tweak building system settings or automatically turn off lights when it determines they are not being used. Numerous case studies demonstrate energy consumption reductions of over 10% or more through AI-powered energy management systems.

Another especially promising area is occupancy management. AI systems use sensors to track when and how different building areas are used. These sensors include cell phones, radar, ultrasound, and infrared to count people and track their movements accurately but anonymously. This data can be used to optimize space utilization, raise energy efficiency, and improve overall building management.

For example, managers can identify unused areas of a building and turn off lights, heating, and cooling in those areas, saving energy and money. Moreover, by tracking occupancy levels, managers can make better decisions about how to allocate space or free it for new purposes. Occupancy sensors can also be deployed to enhance security, such as learning to detect suspicious behavior or optimizing security patrols.

Technology Should Enhance Not Replace Tenant Engagement

Property managers may find AI-powered systems particularly appealing as they can automate a wide variety of routine functions, freeing up staff to focus on more strategic tasks and personal interactions. As AI takes over the mundane, property managers will have the opportunity to optimize operations, enhance efficiency, and elevate the overall tenant experience. In a previous blog, Grace Hill discussed how apartment managers could use ChatGPT — one of the most widely-known AI apps — to improve or streamline basic property management functions such as customer service, marketing, and drafting simple documents like leases.

Still, caution is advised at this early date, especially for functions dealing directly with tenants or other members of the public. General AI systems such as Bard and ChatGPT frequently give out incorrect or offensive information. Any system must be carefully trained and thoroughly vetted before being deployed and interacting with real people. 

AI has the potential to revolutionize how buildings are designed, operated, and maintained, but it is not yet able to replace the “human touch.” The most successful organizations will leverage technology as a tool, while not allowing it to undermine personal service. Studies show a direct correlation between tenant satisfaction and lease renewals. In fact, tenants with a high overall satisfaction level with property management are 3.6 times more likely to renew as compared to dissatisfied tenants.1 Furthermore, tenants who rate overall satisfaction 1 point higher show future overall vacancy decrease by 6.7%.2  

These compelling stats beg the question: How will CRE organizations know if they have the right balance of technology and service? Relying too heavily on AI or other impersonal technology solutions could put overall tenant satisfaction at risk, while not investing in potential operational efficiencies can impact the bottom line. The best solution is to keep your finger on the pulse of your tenants’ satisfaction levels with ongoing communication and unbiased surveys. 

With vacancies increasing and tenant needs evolving, it’s even more important to understand what your tenants really want. Surveys offer essential insight into tenant sentiment, especially when occupancies are low, so you can determine the right balance of property, technology, and staff investments that will lead to increased tenant satisfaction and renewals.

 See how Grace Hill’s industry-leading survey tools can help drive tenant satisfaction to optimize your operations and elevate your property.

 

Footnotes:

  1. Grace Hill, KingsleySurveys, November 2023
  2. Infographic Tenant Satisfaction

Andrew J. Nelson is a real estate economist and author at Nelson Economics, focusing on property market dynamics and demographic analysis, as well as research methods and modeling. Andrew is the lead writer for the Urban Land Institute’s annual Emerging Trends in Real Estate publication and a contributing writer for Seeking Alpha and Propmodo Before founding Nelson Economics, he served as Chief U.S. Economist for Colliers International, where he led the national research team. He developed the firm’s economic and property market perspectives and served as the firm’s primary U.S. economic spokesperson in the media and at industry events. Prior to Colliers, Andrew worked at Deutsche Asset Management (RREEF) as Director, Research & Strategy in the Americas, where he managed the U.S. research team and was the retail sector and sustainability specialist.  Andrew has also held a variety of other leadership positions in both the public and private sectors, including Vice President of HOK Advance Strategies, where he served as national practice leader of the Portfolio Services service line; managed a construction-lending program for the World Bank in Russia; held a two-year “Community Builder” fellowship with the U.S. Department of Housing and Urban Development; and managed the regional real estate consulting practice at Deloitte & Touche in San Francisco. Andrew earned a Master of City and Regional Planning degree from the Harvard Kennedy School at Harvard University and a Bachelor of Arts in Economics from Harpur College. Learn more about Andrew Nelson’s background and experience on his LinkedIn page.

Learn More About The Author

Scroll to Top