Artificial intelligence (AI) is bringing sweeping change to a wide variety of industries, and commercial real estate (CRE) is ripe for this technology. From marketing to property management, AI could expedite processes and cut costs in a range of ways. But what exactly is AI? Here’s a primer.
The term “AI” generally refers to using computers to perform complex tasks — like image perception, voice recognition, decision making and problem solving — usually thought to require human intelligence. Several types of technologies fall under the AI umbrella, including:
1. Machine learning. Machine learning is an iterative process where machines improve their performance in a specific task over time with little or no programming or human intervention. Machine learning can, for example, predict a home’s closing time based on factors such as season and market cycles.
2. Natural language processing (NLP). This uses algorithms to analyze unstructured human language in documents, emails, texts, conversation or otherwise. Loan officers might use it to locate specific information in a document based on the words surrounding that information.
3. Robotic process automation (RPA). RPA automates time-consuming repetitive manual tasks that don’t require decision making, based on business rules and structured inputs. It could, for example, streamline property searches.
It’s easy to see why AI is primed to revolutionize all kinds of business processes.
AI in the world of CRE
Numerous functions at the core of CRE can benefit from AI, including:
Marketing. Property owners, leasing agents, and brokers can use AI to aggregate data from across the Internet to develop intelligence on markets, competitors and potential buyers and sellers. Machine learning can help identify the optimal media avenues to reach target audiences. It also can produce better pricing by predicting demand based on factors such as location and property features. Chatbots — AI texting or auditory programs — can more economically handle routine inquiries from potential buyers or tenants, create profiles and schedule appointments.
Deal matching. AI could improve deal matching in multiple ways. Early on, RPA can collect and process data to rule out mismatches before much time or money is wasted. Machine learning can evaluate risk and make financial projections for properties, warding off would-be investors from properties that don’t satisfy their investment criteria. It also can analyze past transactions to make predictions about the likelihood of a sale between specific parties. NLP can quickly scan documents and identify potential red flags, eliminating the need for prolonged manual due diligence.
Property management. AI promises to produce significant savings when it comes to property management, especially in the area of energy costs. The spread of the so-called “Internet of Things” — meaning the networking of people, sensors and objects to automatically collect, exchange, and apply data — is already paving the way.
Data sensors in building systems allow for real-time adjustments to temperature, lighting and similar controls. This data also can drive predictive analytics that inform decisions about the maintenance and replacement of systems, while robots can check on and possibly repair structural damage.
Chatbots can play a role in property management, too. For example, they make it easier to communicate with tenants promptly and even provide concierge-type services. This may lead to increased tenant satisfaction and attract new tenants.
Of course, these advances aren’t without costs. Property owners will need to invest in enhanced cybersecurity to protect data and access to automation systems. Older buildings also may require some infrastructure updating to take advantage of the new technologies.
The future is now
Artificial intelligence is no longer just a wild idea in the minds of science fiction fans. It’s reshaping many industries and is poised to do the same to CRE. Savvy owners, developers and investors need to stay abreast of the developments to make the most of them.
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