The impact of technology on the commercial real estate (CRE) industry is a vast subject. With over 30 years of IT and leadership experience, Venkat Kandru, Stream’s Chief Digital and Information Officer, discusses how Artificial Intelligence and Machine Learning might impact the CRE world. In this, the first of a two-part series, we explore the benefits of AI in CRE.
Will Robots Replace Brokers?
First, we should be clear in our belief that robots will not replace brokers. They just don’t look good in a suit. When we think about how work across all industries will change, we need to think about how Artificial Intelligence (AI) and Machine Learning (ML) can tackle some of our tasks, not about how robots will replace us. To consider how the CRE industry could benefit from embracing this technology, let’s talk about the role AI might play, and then what actionable and effective programming can be created to make us better at our jobs. As technology advances, will the machines take over our deals, our properties, and even our jobs? Let’s take a look.
What Role Should Artificial Intelligence Play in CRE?
The continued adoption of AI and ML technologies will transform the way we work, especially in industries like finance, banking, and real estate. The CRE industry is in a position to leverage AI and ML technologies to reduce costs, increase productivity, identify risk, and minimize errors.
A report by Gartner in 2019 revealed that 37% of organizations have already implemented AI in some form. That was up 270% from just 10% in 2015. But what is the role of AI and ML across the commercial real estate world?
AI is any machine that can follow a set of intelligent instructions, typically working on a cycle. ML is where it gets exciting. IBM provides a clear breakdown of different types of ML. There is limitless potential for ML, it can be described as a robotic brain, a system that can decide on how to proceed based on inputs, patterns, and desired outcomes. It learns based on data inputs and programming and is a pattern-seeking, problem-solving tool based on patterns to predict performance.
Understanding the Applications for CRE
There are so many applications across the CRE industry. Here, we examine property management operations and in part 2 of this series, Data in CRE, we’ll delve further into building design, construction, and brokerage.
Operations: Battling the Perfect Storm
In general, AI is useful to increase operational efficiencies, provided we have gathered good, meaningful historical data about our operations. For example, building operations can be monitored monthly, weekly, on a seasonal basis, or during certain unexpected events.
How can operations be affected and how does AI help? A great example of operational efficiencies is the big freeze we experienced throughout the central part of the U.S. in February, which killed dozens and resulted in billions of dollars of damage. The Washington Post reported that the temperatures were consistent with what has been seen and monitored over the past four decades. Across the region, many systems failed because they relied too heavily on current and recent data, ignoring a low probability as no probability. Systems simply were not programmed to manage or adapt to the challenges of such an unlikely event. A repeat of the big freeze seems unlikely, but it was neither unprecedented nor unforeseeable. More simply, with more awareness, with better tools and analysis, we could have been more prepared.
A better approach is operational preparedness. Being ready both for predictable and unlikely weather events is crucial, but operational intelligence when it comes to building management also includes daily management and efficiencies. Sustainability, wellness, and budgetary benefits are achieved by monitoring and controlling elements such as energy usage, airflow, and occupancy.
AI takes data from multiple sources to identify patterns, trends, and probabilities. Operations can be programmed to shut down and manage the water flow, to make heating or lighting changes, or even to tell maintenance when a bulb is out (and to automatically order a replacement). These actions are all possible, provided we establish data channels, sensors, connectivity, and an AI engine that can determine and communicate the right actions throughout our buildings.
Is AI coming for your job?
AI is not anticipated to replace people in CRE. However, we do see AI playing a complementary role to CRE professionals. AI can assist us in making decisions—it doesn’t replace us as the decision-makers. AI provides an unbiased perspective, based on what the data shows. It provides a possible set of actions and outcomes like a roadmap to rely on, or not—it is still up to people, with the ability to evaluate the situation, to take the information the data provides, and decide on a course of action.
Does all this mean job losses? Not necessarily. While computers can take over repetitive tasks, which are predictable and require only basic cognitive skills, more complex functions such as management, creative and social endeavors cannot be managed by technology. At least not yet.
Automation of repetitive activities, the predictable or mundane tasks give us more time to focus on what is important and what is more enjoyable. We can focus more on the macro than the micro. To be successful in the CRE world, and, in almost every business, that means building relationships, gaining trust, understanding the market, and to remain in business—keeping your clients ahead.
Next, in this two-part series Data in CRE, we’ll explore data, analytics, and the future of the industry.
Venkat Kandru is the Chief Digital and Information Officer for Stream Realty Partners. Venkat joined the firm in 2019 bringing to Stream over 30+ years of information technology and leadership experience. He is currently responsible for providing oversight, management, and direction to the firm’s digital transformation across the various segments of Stream’s service lines nationally.