AI & Automation

How AI is Transforming Property Management

Read time
7 MINS
Published
March 5, 2021
AI for property management

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 in the real estate sector by answering the following questions:

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What is True AI in property management?

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:

1. Narrow or Domain-specific AI for property management

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.

2. Hybrid AI or Limited Memory AI

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.  

For example:

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.  

3. General or Strong Artificial Intelligence

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.  

For example:

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.  

Artificial Intelligence in Property Management

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 in real estate.  

Artificial intelligence in real estate 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.  

property management ai
Automation and AI in property management

How is AI Automating Communication in Property Management?

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.

ai property management tools
Benefits of property management automation for lead comms

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.  

Difference between Fake/Dumb Bots and True AI Chatbots

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.  

For example:

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.

ai leasing assistant
dumb bots vs true AI

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Will AI Replace Property Managers?

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.  

FAQs

How does AI for property management improve maintenance management?

AI for property management improves maintenance management by predicting maintenance needs, scheduling repairs, and monitoring the condition of properties. AI algorithms can analyze data from various sensors and maintenance logs to predict when equipment or infrastructure is likely to fail, allowing for proactive repairs. This minimizes downtime and prevents costly emergency repairs.

Can AI for property management help in optimizing rental pricing?

Yes, AI for property management can help optimize rental pricing by analyzing market trends, local demand, property features, and historical data. AI systems can provide dynamic pricing recommendations that maximize occupancy rates and rental income. By continuously monitoring the market, AI ensures that rental prices remain competitive and aligned with current market conditions.

How does AI for property management enhance security?

AI for property management enhances security by integrating with surveillance systems, access control, and anomaly detection. AI-powered surveillance can identify suspicious activities, unauthorized access, and potential security breaches in real-time. It can also automate alerts and responses, ensuring swift action to mitigate security risks.

What role does AI for property management play in energy management?

AI for property management plays a significant role in energy management by optimizing energy usage, reducing costs, and enhancing sustainability. AI systems can analyze energy consumption patterns, predict peak usage times, and automate heating, cooling, and lighting systems. This ensures efficient energy use and reduces waste, leading to lower utility bills and a smaller carbon footprint.

Can AI for property management assist with financial management?

Yes, AI for property management can assist with financial management by automating accounting tasks, generating financial reports, and providing insights into cash flow and budget management. AI tools can track income and expenses, manage invoices, and forecast financial performance. This helps property managers maintain accurate financial records and make informed financial decisions.

How does AI for property management impact tenant satisfaction and retention?

AI for property management impacts tenant satisfaction and retention by providing quick responses to tenant inquiries, addressing maintenance issues promptly, and personalizing tenant experiences. AI systems can analyze tenant feedback, predict tenant needs, and offer customized services. This enhances tenant satisfaction, leading to higher retention rates and positive tenant relationships.

Is AI for property management integration in property management software difficult?

AI for property management integration in property management software is becoming increasingly straightforward due to advancements in technology and the availability of user-friendly AI solutions. Many property management software providers offer AI-powered features that can be easily integrated into existing systems. Property managers can work with vendors to ensure smooth implementation and minimal disruption to operations.

What are the ethical considerations of using AI for property management?

The ethical considerations of using AI for property management include data privacy, transparency, and fairness. Property managers must ensure that AI systems comply with data protection regulations and that tenant data is secure. Transparency in AI decision-making processes and addressing biases in AI algorithms are also crucial to maintain trust and fairness in tenant interactions.

How can AI for property management assist with legal compliance?

AI for property management can assist with legal compliance by automating document management, tracking regulatory changes, and ensuring adherence to legal requirements. AI systems can generate and review lease agreements, monitor compliance deadlines, and provide alerts for any potential legal issues. This helps property managers stay compliant with laws and regulations, reducing the risk of legal disputes.

What are the future trends of AI for property management?

The future trends of AI for property management include advanced predictive analytics, increased automation of administrative tasks, and the integration of AI with other emerging technologies like the Internet of Things (IoT) and blockchain. AI will continue to evolve, offering more sophisticated tools for property management, enhancing operational efficiency, and transforming the industry.

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Author
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