The real estate industry has been adopting digitalization for quite some time now. COVID-19 further served as an enabler, boosting adoption rates of technology across the industry.
However, the industry still holds huge potential for growth leveraging technology and workflow automation, making it lucrative for tech-based startups to enter.
Last year alone, the worldwide funding of tech-based startups operating in the real estate industry skyrocketed by 36%. Amid the surge in ‘PropTech’, some terminology that is starting to make its rounds in the industry is Artificial Intelligence or ‘AI’.
Even though Artificial Intelligence is here to stay, many are still confused about its practical applications, and how is it changing the current dynamics of the real estate industry.
This blog will help you to stay on the bleeding-edge of what the future holds for AI technology in the real estate sector by answering the following questions:
Despite tons of articles being published on AI, we still find ourselves questioning the legitimacy of AI’s existence in the real world.
Many thanks to the media for over exaggerating the pitfalls of Artificial Intelligence, making it synonymous with evil robots trying to take over the world.
So... what really is Artificial Intelligence?
In layman’s terms, any machine or software that is capable of solving a problem, automating a task, or appearing to possess similar cognitive abilities as human beings, can be considered Artificial Intelligence.
Artificial intelligence can be categorized into three broad categories:
Domain-specific AI can only perform the task it is purpose-built for, be it reporting weather changes, minimizing accounting errors, or playing chess. This kind of artificial intelligence is what scientists and researchers have achieved up till now.
Narrow AI is also known as Weak AI for its inability to perform actions that are beyond its limited scope.
For example, smarter home robot IROBOT, uses AI to identify smart routes for cleaning. It is a domain specific AI because it is designed to perform only one task that is vacuuming.
Currently, narrow AI or domain-specific AI is the only dominant variant of Artificial Intelligence in the real estate industry. The weak AI can be further classified into two more sub-categories:
Reactive Artificial Intelligence is the simplest form of Artificial Intelligence. It uses a highly specific range of data, which ultimately limits the scope of its operations.
Netflix’s recommendation engine uses a reactive AI to predict the viewer’s next series/movie. It helps Netflix in providing a more personalized experience to its users.
If person A watches shows like “Game of Thrones” or “Die Hard” they are most likely to watch movies or shows in the “thriller or action” genre. Netflix’s reactive AI analyzes person A’s viewing history and then recommends the most relevant titles.
However, the algorithms become more complicated once the number of variables increase. Such an algorithm would take in data about the viewer’s age, interests, and gender, plot similarities, actors/actresses, and watch history into account when making predictions.
Hybrid AI is the most sophisticated form of Artificial Intelligence we see today. It can memorize data and improve predictions over time based on past experiences.
This is the highest level of Artificial Intelligence researchers have achieved yet. Limited Memory AI uses supervised learning techniques such as Machine Learning (ML) and Natural Language Processing (NLP) for training algorithms.
Software or machines using hybrid Artificial Intelligence can make decisions based on context and can truly automate operations for the end-user.
Google Assistant, Siri, Alexa, etc. all use Natural Language Processing (NLP) to translate spoken language into a text that is easily ingested and further processed by computers.
Similarly, self-driving cars use Hybrid AI to learn different responses based on unique circumstances. They require machine learning to train the vehicles and interpret signals based on changes in the environment.
It is Hybrid Artificial Intelligence that makes self-driving cars safer on the roads, as they can instantly adjust to environmental changes whenever necessary and make instant decisions with higher accuracy.
Strong Artificial Intelligence refers to machines that almost possess human-like intelligence and are designed to understand a broad scope of knowledge, similar to humans. General AI consists of multiple, or “deep” machine learning models that can replicate human behavior, self-learn, and can independently use past knowledge to make better decisions in the future based on outcomes.
Strong AI, hasn’t yet been achieved by any independent researcher, or major company. Our lack of comprehensive understanding how the human brain functions, is a major impediment for current researchers.
General Artificial intelligence will be capable of problem-solving, decision making, strategic planning, self-learning, and making decisions for itself in cases of uncertainty. But ultimately, someone has to program these things to get these processes started.
A hypothetical example of general AI would be “Jarvis”, Tony Stark’s robotic assistant in Marvel’s Avengers. Jarvis is capable of reacting to new and previously unknown experiences in an intelligent, sophisticated manner. While we already have robotic assistants such as Siri, or Alexa, they are ultimately limited to the circumstances developers have programmed.
Super AI is the ultimate goal of Artificial Intelligence research. It refers to machines or software that are capable of outclassing humans in every way.
They will learn faster, make better decisions, and possess more memory. Super Artificial Intelligence is expected to be self-aware and has desires, emotions, and needs of its own.
Machines with super artificial intelligence will be able to negotiate with humans and make decisions based on their understanding – meaning they won’t require someone to control their actions.
This kind of AI is only hypothetically seen in movies yet, as no researcher or scientist knows when exactly it will be achieved.
Super AI is the destructive AI we commonly see in media. Examples could be movies like ‘SkyNet’ in The Terminator, The Matrix, or various characters in Star Wars where AI act independently on their own, possess emotions and can train other AI itself.
The artificial intelligence industry is growing at an ever-increasing rate, and revolutionizing the way things work in most sectors. The real estate industry is not an exception when it comes to benefitting from AI and its limitless applications.
By 2025, the AI industry is predicted to reach $190.61 billion, resulting in an inevitable boom in AI technology within the real estate industry.
Artificial intelligence in the real estate industry can assist investors, property managers, brokers, or clients make better business decisions and achieve desired results.
The new wave of ‘PropTech’ is also helping property managers save time from the day-to-day mundane tasks and focus their time on growing portfolios instead.
Property managers have been using property management software for years to assist them with daily activities. It is only a natural extension to adopt artificial intelligence for improving the current software and making the job of property managers easier.
Communication between prospective renters and leasing agents is an important aspect of property management and AI based chatbots can automate it effectively and efficiently.
The AI-powered chatbots use NLP to interpret renter inquiries and intentions using machine learning to deliver accurate and diverse responses, learning from past interactions.
So, how do these smart AI assistants automate communication?
Once property managers upload a rental advertisement on listing sites, renter inquiries start pouring into their inboxes. On average, a leasing agent receives 100+ rental inquiry emails every day, which goes up to 300 in the multi-family industry.
90% of these emails are similar in nature and responding to each email individually takes up about 75% of a leasing team’s time. Alternatively, property managers resort to outsourcing the entire communication process or hiring virtual leasing agents.
A smart leasing assistant, like River, costs you four times less and is twice as fast. The best part about River is that it's active 24/7 so there is no chance of missing any renter leads after hours or even on weekends!
These intelligent chatbots can pre-qualify renters and schedule tours right into the leasing agents personal calendars within their desired time frames. They also follow-up with prospective renters before scheduling a tour, reducing the number of no-shows for leasing agents.
As the industry is progressing towards technology, unfortunately, the number of mimics claiming to use AI and machine learning technology is also increasing.
As a property manager, you need to differentiate between fake and true AI before investing in any bot to ensure it is worth the investment.
Fake bots do not use machine learning, instead, they use a limited rule-based approach for renter communication. These bots are similar to Facebook messenger bots which send automated messages and have some pre-set answers to pre-defined user inquiries.
The absence of context makes these bots less valuable – as they can’t hold real-time conversations with prospective renters.
If a renter questions about whether pets are allowed in an apartment, the fake bot will respond with a simple Yes or No. However, if a renter inquires “Is a Pitbull allowed?” instead, the fake bot will fail to respond.
The reason is these bots are conditioned to answer only the inquiries or keywords that are fed to them. Consequently, failing to answer inquiries beyond their pre-defined responses.
On the other hand, a true Artificial Intelligence powered chatbot actively learns from each user interaction and gets better at understanding the inquirer’s intent. It becomes more intelligent with continuous training and is capable of answering renter inquiries in greater detail.
The most straightforward answer to this question is No.
Artificial Intelligence in real estate is designed to complement existing software or processes to increase operational efficiency and streamline your business operations.
Its goal is to automate the repetitive tasks in your to-do list, so you can focus more on the relationship-building aspect of your jobs.
Rather than spending your energy on monotonous tasks, you can channel it towards providing a highly personalized experience to your current tenants or dealing with clients to grow your portfolio.
No one really knows when scientists and researchers will achieve General or Super intelligent AI. So, it is safe to say that AI will not be replacing humans at real estate jobs any time soon.
Do you know that 157 US companies with $50M liabilities filed for chapter 11 bankruptcy due to COVID-19? If you don’t want to be on that list, keep reading our article, and learn the best ways to manage your property management business remotely.
A quick response to rental inquiries is the first step in ensuring that your vacant units are filled with qualified renters. A failure to do so could risk property managers losing out on leads and accumulate lost rent.
Why spend five times more money finding new tenants when you can retain the old ones who are 70% more likely to stay? Read and implement our expert advice for better tenant retention and a high rental occupancy rate.