How AI is Reshaping CRE

Tech You Can Implement

By Lee Ann Stiff on Aug 15, 2024 in Technology

AI is top of mind across the real estate industry, and the business case for AI in CRE has become clear. CRE stakeholders embracing AI’s impact on the industry are already employing data-driven approaches to decision making while leveraging AI to improve day to day operations including optimized AP processing and customer service. Following are three ways AI is revolutionizing CRE with tech you can implement now.

Chatbots

A chatbot is any software solution that simulates conversation using natural language through text or voice interaction. OpenAI’s ChatGPT, Google’s Gemini, Meta’s Llama and Anthropic’s Claude are examples of large language models (LLMs), which draw on vast amounts of data to predict the next word and answer a question or suggest a solution to a problem. Common uses for ChatGPT include writing emails, proofreading and other everyday tasks. Businesses are employing chatbots most often for customer service. In the multifamily sector, owners are using this type of AI to respond to resident questions and maintenance requests, as well as to provide prospects with information about properties.

Research shows that a smart chatbot can significantly reduce the number of days it takes to convert a lead to a lease. With regard to saving staff time and optimizing efficiency for maintenance processes, during a call to report a clogged sink, for example, a chatbot can take the resident through steps to resolve the problem before issuing a maintenance request or connecting them with a property team member. Managers at office, retail and industrial properties can use ChatGPT in similar ways. Yardi employs ChatGPT in its natural language processing solution to improve the accuracy of its responses to client questions. Yardi’s chatbot now resolves 80 percent of inquiries that previously required the attention of a customer service representative. As a result, team members are freed up to tackle requests and issues where solutions aren’t readily available and more expertise is required.

Web content solutions

A widespread lack of website compliance with the Americans with Disabilities Act (ADA) touched off a wave of federal legal challenges beginning in 2018. By creating environments where website users can participate equally, operators can avoid this legal risk and foster seamless interaction with digital content. In recent years, emerging AI platforms in web development have begun to provide solutions to address ADA compliance issues, according to Equally AI, a developer of website accessibility software.

Screen readers and natural language processing can analyze and interpret web content, providing auditory cues to assist users with visual impairments, for example, while conversational AI speech recognition capabilities allow users with mobility impairments to interact with websites through voice commands. AI-powered captions and transcriptions provide similar benefits to those with hearing problems. Other solutions include AI-driven interface enhancements such as adaptive design and intelligent navigation, which can adapt websites based on user preferences and behaviors.

Machine learning

In recent years, Yardi employed a full-service invoice processing center for 60 million annual client invoices, where teams would manually scan, key and code invoices into client environments. This would then initiate the workflow for invoice approval. But over the last three years, the company has migrated that activity to machine learning. Vendor names, invoice numbers and line item details are now encoded into the accounting systems for fully automated processing. Employing machine learning to this tedious, time-consuming task has not only improved accuracy but has also produced cost savings, which Yardi is passing onto clients. “These are very simple tasks, but the machines need a lot of data and experience to achieve a high level of accuracy,” said Brian Sutherland, a Yardi vice president. “We certainly have that data at scale.”

Similar endeavors Yardi is working on include a lease extraction solution. That will pair machine learning with a chatbot to identify, collect and organize lease expiration dates, rent step-ups, options and other pertinent information that is typically buried in dense contract verbiage, making it difficult to locate. The technology will then format the information in abstracts for easy retrieval by clients.

Data to visualize and drive performance

Chatbots, machine learning, large language models and other AI technologies are already helping adopters envision business and industry-wide evolution. AI will quickly move beyond simply automating data-intensive manual tasks to become a new type of personal assistant. In this role, it will be able to crunch data about building permits, occupancy, the cost of capital, labor costs, rental rates and trends, comparable sales, demographics and other metrics. Having digested all those variables, AI tools will be able to advise landlords, investors, executives and property managers on investment and development, rent pricing, concessions and capital improvements among other complex decisions.

Moving forward, AI’s effectiveness relies on harnessing and analyzing large quantities of data. While information aggregators have refined their methods over the last few years, the CRE industry remains somewhat opaque. Fortunately, the information needed to successfully enable AI solutions exists – the key is to structure it for easy consumption and connect it for effective leveraging. We have a lot of data at our fingertips, and our focus is to expose the right data at the right time to the right people, along with prescriptions to drive enhanced CRE performance.

Learn more about AI solutions for CRE.