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Revolutionizing Multifamily Management: The Power of AI and Predictive Analytics

Written by Veena Jetti | Oct 17, 2023 1:34:40 PM

The management of multifamily investments and operations is changing fast. Deloitte forecasts global AI spending will be $97.9 billion in 2023. Across all the multifamily projects that I am involved in, the trend to use AI for various aspects of the project go/no-go has moved from the nice-to-have to the must-have column.  

Predictive analytics and AI can be applied in various aspects of multifamily, from market trend forecasting, pricing, and risk assessment to lead generation and customer service. Fusing these technologies allows for a more data-driven and efficient approach to multifamily management.

For example, in a recent project that I was involved in, the usual two-dimensional data such as location and demographic trends alone would have pointed to a “no-go” decision. However, when other variables such as job migration, industry sector growth, long-term trends, local government policies, tax regimes, and others were factored in and analyzed using an AI algorithm, the “no-go” decision was reversed. We are continuing to learn and adapt to the power of AI and as time goes on, our experience in this space will allow us to fully appreciate and apply AI in multifamily. 

The following areas in multifamily are amenable to AI-driven systems. Various software are available in these categories, but you will need to evaluate each according to your specific needs. Be sure to consider security, cost, benefits, efficiency, accuracy, and scalability when deciding which AI solutions to implement.

1. Market Trend Forecasting

AI can analyze vast amounts of data, including historical real estate prices, demographic trends, and economic indicators, to forecast future market trends. Tools like Zillow's Zestimate and Redfin's automated valuation tools use predictive analytics to estimate real estate value. 

2. Property Valuation and Pricing

Predictive analytics can improve accuracy in estimating property values by analyzing location, property characteristics, and historical sales data. Machine learning algorithms can identify complex patterns and relationships among these factors to provide more accurate price suggestions. Investors may choose to utilize solutions like Skyline AI and Enodo to assist in underwriting.

3. Risk Assessment

AI can help assess the risks associated with real estate investments by analyzing historical data, macroeconomic indicators, and property-specific factors. Using AI technology allows investors to analyze longer periods while still taking into account compounding factors without any additional human power needed. This can enable investors to make better-informed decisions and mitigate potential losses while maximizing efficiency. Axiometrics, a part of RealPage, has tools for risk assessment.

4. Lead Generation

Machine-learning platforms, like Hyro, can identify potential clients based on their online behavior and other demographic and psychographic factors. These algorithms can prioritize those who are likely to convert, helping multifamily managers focus their efforts more efficiently.

5. Customer Service

AI-powered Chatbots can provide instant customer service, answer common queries, and even schedule appointments, providing a better experience for potential renters.

6. Property Management

AI can be used in innovative management technology to increase the value and attractiveness of a property. Every physical object that connects to the internet and sends data back to the manufacturer is a part of the Internet of Things (IoT). AI predictive maintenance can use IoT data to predict when a system might fail and need maintenance. This proactive approach helps property managers address problems promptly, minimize disruptions, and reduce maintenance costs.

7. Intelligent Energy Management

AI can optimize energy consumption by analyzing data from smart meters, weather forecasts, occupancy patterns, and historical data. It can automatically adjust temperature settings, lighting, and other energy-consuming systems to minimize waste, lower utility bills, and reduce the environmental footprint. Some investors choose to install smart thermometers in each unit that learn tenant patterns during the day and automatically adjust the temperature accordingly. This increases energy savings and saves you and your tenant money.

8. Enhanced Security and Safety

AI-powered surveillance systems with facial recognition and object detection capabilities can monitor common areas, entrances, and exits. These systems can alert property managers about suspicious activities, unauthorized access, or potential safety hazards, improving security and resident safety.

9. Personalized Tenant Experiences

AI can collect and analyze tenant data to understand preferences and provide personalized recommendations. Property management systems can leverage AI to streamline communication, offer customized services, and optimize amenities to cater to individual needs.

Conclusion 

Remember, as with any technological adoption, associated costs, potential risks, and data privacy concerns need to be carefully considered. In addition, training and implementation could also pose challenges. So, while I fully believe AI will be a growing part of our day-to-day life in multifamily investing, it is essential to evaluate each situation carefully when leveraging predictive analytics and AI.

 

About the Author:

Veena Jetti is the founding partner of Vive Funds, a unique commercial real estate firm that specializes in curating conservative opportunities for investors.

 

Disclaimer:

The views and opinions expressed in this blog post are provided for informational purposes only and should not be construed as an offer to buy or sell any securities or to make or consider any investment or course of action.