Finally forced to embrace innovative solutions during the pandemic, multifamily made tremendous strides in terms of technology implementations over the past two years. Automations flourished as operators sought out contactless solutions. New operational efficiencies emerged as platforms were deployed to accommodate a remote workforce.
Initially, however, multifamily left its guard up when it came to artificial intelligence (AI). Now, with a better understanding of AI and its potential roles in leasing, operations, and property performance, industry skepticism is gradually dissolving.
Commercial real estate software and data engineer Sudip Shekhawat has spent the past two decades building software solutions and creating and scaling cloud-based statistical analysis system (SAS) solutions in the multifamily space.
He led a global team of more than 200 associates at property management software firm RealPage, focusing on revenue management, business intelligence, data analytics and mergers.
Now senior vice president of engineering at insurtech firm LeaseLock, Shekhawat is spearheading software engineering and machine learning initiatives to scale the company’s insurtech solution alongside ambitious growth objectives.
He said that while multifamily has finally opened the door to AI innovations, the industry first had to overcome its own misunderstandings of the technology.
“AI goes back well beyond 20-25 years, when all we knew about AI came from ‘The Terminator’. We really just didn’t exactly know how to use it,” Shekhawat said. “To me, ‘augmented intelligence’ sums it up better. That says that anything you can do as a human being we can augment the intelligence positions through machine learning and machine processes.”
Data Is the Foundation of AI & Machine Learning
Shekhawat pointed out that thanks to self-driving vehicles and the widespread use of chatbots, most people now have a basic idea of how the technology works. In his experience, AI is most often misunderstood when it is confused with analytics applications, or through assumptions that the technology is too complex and out of reach.
“It’s critical to remember that without data, there is no AI,” Shekhawat noted. “The recording of data and the access to those recordings, as well as the digitization of more processes helps us to build AI and enhance machine learning. We are sitting on this wealth of data supplied by property management systems. There is an immense amount of untapped potential in that data.”
AI gained its first foothold in multifamily in leasing and marketing, Shekhawat said the opportunities to optimize operations through AI go much further.
Data-Driven AI Is Transforming Risk Management
“There has been a lot of focus on using AI for human interactions in the leasing offices and organizationally, with chatbots, as well as lead generation and lead management,” Shekhawat explained. “It’s making more inroads to creating better customer experiences, increasing operating efficiencies and improving decision making. With better decision-making, we can optimize asset performance and better manage risk. That’s where I think AI is going, taking on risk management.”
Shekhawat believes that through the use of AI in fintech and insurtech platforms, multifamily companies can make more accurate forecasts for their assets. When AI has access to the data and analytics, machine learning can drastically improve the process of underwriting, asset insurance and claims.
“The application for AI in insurtech has been developing a faster claims process and quicker fraud detection,” Shekhawat said. “Those are two areas where other industries have seen great success with AI.”
Multifamily Data Protection Challenges
As more processes in multifamily are digitized, AI has the potential to continually improve property performance. However, Shekhawat warned that the increasing data volume will create challenges for the industry in terms of data storage and protection.
“Virtually all property management is through software right now. Each transaction, each event is being recorded somewhere and generating a data point,” he said. “Each day, we get exponentially more data points. With so much data, the challenge is how to store and access the data securely.”
The increasing data volume can slow down data analysis and make it difficult to determine which data points to prioritize. Operators are strategically deploying AI to run multiple scenarios, significantly streamlining the process to identify the most optimal business approaches.
“AI enables you to make decisions faster because you’re not looking at the data on a granular level,” Shekhawat said. “You’re not just looking at raw data over a set period of time. AI should save time and impact the bottom line. It should continue optimizing and improving asset value.”
Overcoming Data Gaps Through Fully Integrated Solutions
Shekhawat stressed the importance of AI supplier/partner selection, particularly in terms of integrations and their ability to overcome gaps in the data.
“Do they have sound and seamless integrations, or is that going to take time to develop? Are they aligned with your organization’s long-term focus? These are questions that must be answered,” Shekhawat suggested. “Suppliers must be data driven, think data first, and be a data organization. As suppliers, we have the responsibility of solving for missing data points.”
Moving forward, Shekhawat said multifamily must seek out opportunities in the lease lifecycle that are optimizable through AI. He said it is imperative to look outside the industry for potential solutions and partnerships. Most importantly, organizations need the right processes and people in place to collect and record the important data required to effectively derive the benefits of AI.
Shekhawat concluded, “Fifteen years back, somebody said, ‘Data is the new oil.’ They were so right. Now, what you do with the data is the new oil. Data and AI technology will enable firms to make more informed decisions, but I think AI is still in its infancy in multifamily. We have a lot of runway yet to be covered.”
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