Yardi Breeze is on the forefront of tech evolution in property management. Automation and artificial intelligence solutions are being touted as the future of commercial real estate. Still, we know that AI in property management is undoubtably in the first wave of adoption. From improving productivity and slashing operational costs, to freeing up more time for human-led creativity, a range of innovative tools promise to disrupt the asset class in the coming decade.
Despite critics pointing to potential job insecurity, an increasing number of firms are looking to the technology as a key differentiator to stand out against the crowd. In a recent interview, Rob Teel, president of global solutions at Yardi, answered questions about the main factors driving AI adoption and future growth.
How much appetite is there for AI in commercial real estate?
When we look at the impact of AI today, it is undeniably at the proof-of-concept phase. To say that anybody has fully figured out AI in property management would be premature. Everyone is launching small projects to trial the new technology. Almost all our clients have projects underway to test the capabilities of AI.
ChatGPT made a huge impact last year. Now, vendors are now trying to figure out how they can monetize AI and what future budgets may look like. Firms are experimenting, but it is likely too early to expect much budgeting just yet. I think it will probably be 2024 or 2025 before firms formally start to do so.
Regardless, AI-aided digital assistance is set to grow substantially over the coming years. Microsoft has taken an interesting approach with the launch of its 365 Copilot icon to help assist their Office 365 customers. My bet is that enterprise-ready AI in the future will be embedded into our solutions in a similar way across accounting, performance management, fundraising and investor portals. AI will be blended into those solutions, and each will have something specific to justify the cost. I see it propping up the value of our existing products.
How might regulations and data protection affect the growth story?
If you take the example of abstracting a lease, there is private information that must be considered. If you are trading information or having a chat session with an investor or a tenant via an AI tool, that data needs to be safely stored. When it comes to multifamily, there are already strict rules in place regarding personal data.
Any time we connect a prospect or customer to their personal data, that must be monitored closely to ensure proper data security, which has always been core to our business. It’s the same with AI. If a customer opens a chat session or retrieves data, we need to be able to protect against any type of intrusion. From our investor portal, we always monitor the movement of megabytes and if there is anything abnormal, the AI immediately shuts off access. Others are using trend analysis to detect intrusion using AI tools, which highlights the wide range of benefits that AI offers.
What are the main operational benefits of AI?
The first is chatbots. Real estate technology typically starts where you find the highest transaction volume, which currently tends to be in multifamily or short-term rentals. Over the last three years, multifamily has embraced chatbots to help with prospect flow. The technology is valuable, particularly when leasing agents are not available and customers have questions. A prospective tenant may be surfing the web late at night after a long day at work; chatbots are a natural fit and speed up the process of finding a home.
Chatbots can also be applied to commercial properties. For example, a customer may have a leaky faucet, or an investor might wish to call with questions about their returns over a weekend. Customer interaction and automation are a natural fit for chatbots and AI in property management.
The recent focus has been on natural language processing and determining the intent of questions. Do you accept pets? What is the price? When can I move in? Chatbots are important because they can handle two-way communication. The caveat is that responses have typically been stilted, so the next stage is to improve the quality of these chatbot responses. We aim to make the answers appear less robotic and all with the same polite tone.
On content generation with AI in property management
Generation of content is another important benefit. Firms are starting to use AI in pure content creation, particularly for marketing when creating videos with AI-generated voiceovers and engaging text. Floorplans are an obvious area where AI can be used to create more optimal visuals.
There is also a great opportunity to rethink transaction document ingestion. Machine learning can be used to convert an image of text into a machine-readable text format; for example, with invoices from vendors. We are hopeful that ingesting and abstracting documents will be greatly pushed forward by new models of AI.
AI requires large amounts of power to crunch data. How are investors thinking about ESG & sustainability implications?
Our large clients continue to press us on solutions for ESG and sustainability. There is an industry responsibility to understand the impact of AI from an energy consumption standpoint. We also need to think about how AI can help clients reduce their power usage and cut energy costs.
We have already been doing this for many years via machine learning algorithms. This technology can be used by managers to optimize heating, ventilation and air conditioning (HVAC) systems, one of the largest consumption sources of energy in commercial buildings. This can help form a feedback loop to keep improving HVAC systems, and AI can be trained on the best use of a high-power system like HVAC to compare commercial buildings. The benefits of delivering AI far exceed the cost from an energy and ESG standpoint.
What are the key challenges likely to impact future growth?
There have been plenty of exciting technologies that have come and gone in recent years. We thought extensively about whether to invest in various technologies, but many proved to be underwhelming.
In 2014, blockchain enjoyed the same level of buzz that AI in property management is experiencing today. If we look back, it added some transaction and security validity that did not exist before. Still, it did not have the impact that everyone expected. Back then, it was discussed in every conference agenda and executive meeting however it did not particularly impact our clients’ growth and bottom line.
When we think about new technology, whether it can make or save money for our clients has to be the first consideration. While blockchain undoubtably had a positive effect on many sectors, it simply did not do that at scale. AI is a completely different story. Possibly the closest comparison in terms of global impact would be the launch of the web in the 1990s. We never dedicated a large portion of the company’s resources to building blockchain solutions. However, our spending on AI is unlike any technology change I have seen during my career.
How might data quality and availability impact potential growth?
Access to data makes a huge difference in the effectiveness of AI. Our clients are sitting on a mountain of data. This is particularly true if they have rolled out our property management solutions in addition to investment accounting.
They have data around every asset in the portfolio. That includes every fund and investor. In fact, most of our clients also have extensive data around their operations. With a fully deployed ERP stack, including operations, the benefits of AI in property management are limitless.
Rob Teel joined Yardi in 2003 and has been a project and program manager for many multinational implementations. Since 2007, Rob has overseen the product direction and development of Yardi’s investment management, global and commercial product lines. Prior to joining Yardi, he was a consulting manager for Accenture in the ERP (PeopleSoft) and business process outsourcing market sectors. He has been a financial and property management systems consultant for over thirteen years. Rob holds BA degrees in management information systems and finance from Florida State University.
