AI in commercial real estate: the face of digital disruption

AI in commercial real estate

Artificial Intelligence (AI) is transforming manual workflow and disrupting the commercial real estate industry. With AI, the commercial real estate sector can shed its long-established resistance to technological innovation. AI in the commercial real estate industry can boost productivity and lower the cost of property management. Hence, property brokers, agents, buyers and sellers are leveraging AI to identify industry trends, estimate property market value and automate the overall process of property deals and transactions. 

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) refers to the ability of machines and computers to imitate human intelligence and cognitive abilities. AI enables machines to learn from various inputs and experiences and perform manual tasks that previously required human intervention. Machine learning algorithms process huge chunks of data to identify patterns and solve problems, make decisions and predict outcomes.

Artificial Intelligence is the future of humans. With its machine learning and deep learning algorithms, AI is evolving continuously to include various cross-disciplinary approaches under its wings. As a result, today AI serves as the perfect solution to executing manual activities in several industries ranging from healthcare, finance (commercial lending) and real estate. 

A commercial real estate property transaction is usually a tedious, multi-step process involving property search to investments, due diligence, document filling etc. AI streamlines the entire process with the help of its self-learning capabilities and data extraction. As a result, it reduces the overall operation cost and burden of property transactions on brokers, agents and investors.

AI in commercial real estate: use cases

1. Property value estimation

AI aggregates data related to a property to help investors make an informed decision regarding whether or not to purchase a property. 

For instance, the automated valuation model of an AI application gathers data about the location of the property. As a result, interested buyers can access transportation options, area crime rate statistics, etc. Moreover, AI in commercial real estate allows investors to gain insight into minuscule data related to the property.

This includes data regarding energy consumption, market performance, rent, demographic trends, occupancy rates, parking space availability etc. Hence, they can analyse the value of a particular property beforehand.

In addition to this, AI estimates the price fluctuations expected in a particular location and allows investors to calculate an accurate ROI. AI has the ability to crawl huge volumes of data in real time and it continuously learns new information. This enables developers and investors to make better data-driven decisions.

Under a non-AI-managed scenario, such crucial information regarding a property and its value estimation would have been conducted by manual methods. This is generally more time-consuming and expensive. Implementing AI in commercial real estate automates such tasks and brings down operational costs. 

Moreover, brokers and agents often do not have access to such detailed information regarding a property. In such cases, Big data and predictive analytics map past trends and future estimations in real-time to produce actionable insights regarding the asset.

AI in commercial real estate leverages such untapped information that transcends traditional data points.

Hence, investors can compare various properties based on their variables and gain insights into their values. Therefore, investors can exploit AI tools like machine learning and Big Data to estimate the value of the commercial property and make accurate data-based investment decisions.

2. Market analysis

AI is more irreplaceable than ever in conducting an efficient market analysis. Its aggregate algorithms collect various crucial data that help in an accurate market analysis. AI in commercial estate helps in identifying rental trends, occupancy rates, usage statistics and price shifts within a particular market in a certain geographical location. It also tracks demographics that include employment trends and income levels in a certain area.

As a result, investors and developers can understand better where commercial buildings such as offices, retail centres or even multifamily housing can fare better. 

Moreover, the combination of historical trends, predictive analytics and a comparative analysis of multiple properties are particularly useful for CRE investors. This is because when the user inputs market trends data and other related keywords, the machine learning algorithms easily identify the sites and properties for potential investments.

Additionally, AI matches buyers and sellers with properties that best suit their history and preferences after compiling and comparing market data and broker sales records. Therefore, AI in commercial real estate definitely upgrades the existing market data processing techniques.

3. Property Management

Besides property value estimation and market analysis, AI in commercial real estate helps with property management as well. Commercial property managers track a range of tasks including property rentals, lease negotiation, tenant applications, company finances, calculating profit goals, etc.

However, a property manager performs all these tasks manually, which makes traditional property management expensive and time-consuming. As businesses grow and the number of applications surges, property managers run the risk of losing vital information.

AI, on the other hand, automates and digitally manages everything ranging from tenant applications to rentals and maintenance requests. An AI tool can streamline internal processes of property management by organizing all the tasks from data entry to lease abstraction. 

In the case of property owners, AI algorithms can find reliable tenants through their intelligent screening process that analyzes a tenant’s behaviour and track records. This results in reducing vacancy times and tenant turnover rates.

Moreover, owners can opt for building automation solutions that provide energy efficiency upgrades and track the lifecycle of various appliances.

As a result, AI data analytics recognizes the performance patterns of various electronic appliances. It identifies irregularities and alerts the owners of the time frame when an appliance malfunction is likely to occur or when an upgradation is due.

Hence, AI allows owners and property managers to be more proactive in maintaining and refurbishing their properties.

Tenants can use AI chatbots to pay rent, place maintenance requests, and even track their utility usage. As a result, AI in commercial real estate is rebuilding the tenant and owner relationship like never before.

4. Marketing

AI systems streamline commercial real estate marketing strategies. A combination of Customer relationship management, Natural Language Processing (NLP) and AI helps in identifying the target audience and understanding their preferences better.

As a result, AI-based lead management systems enable CRE companies to launch personalized promotions or messages to prospective investors and sellers. 

Companies can create personalized e-mail campaigns, online advertisements, and interactive AI-powered Chatbots that would serve as sales reps. A CRE chatbot can ask the client about their budget, preferences and location.

After gathering the required information, the companies can offer personalized property results directly to the leads. Thus, the marketing campaigns become highly targeted and have the potential to become actually successful.

This is because of an intuitive AI that studies people’s preferences and market analytics to deliver personalized ad campaigns.

On the other hand, in the absence of such crucial data, ad campaigns are generally vague and are often ignored by people because they do not appeal to their interests. As a result, millions of dollars are spent on marketing only to generate few or no leads.

Therefore, AI in commercial real estate not only churns leads but also limits the approach to potential clients. In the process, a CRE company saves time and money with value-add marketing campaigns.

5. CRE underwriting

CRE underwriting is a long-drawn tedious process that consists of huge piles of paperwork and manual labour. The implementation of automation in CRE underwriting accelerates the process.

Underwriting is a crucial part of commercial real estate property deals. Through underwriting, a lender can scan a borrower’s credit history and determine a property’s value. Under ordinary circumstances, these processes are non-automatic and completely manual.

However, AI reduces the downtime of the reviewing process. This is because, it automatically reviews important documents in multiple formats, in under a few seconds.

Besides, AI automation software extracts and classifies crucial data like rent roll and property cash flow data. The huger the database an AI studies, the faster it identifies and reviews a new mortgage opportunity. It studies the past loan records and cash flow/liquidity of a borrower.

Hence, a faster underwriting process determines the profitability of a deal faster and instantly notifies the lenders of credit risk. Moreover, AI also enables tracking and auditing loans and loan portfolio management.

In addition to this, AI also provides accurate information about a property and related predictions and insights on the current and future value of the asset. Hence automated, error-free loan evaluations, and pattern recognition algorithms are revolutionizing the CRE underwriting process.

6. Data management

Commercial real estate operations involve colossal volumes of data. However, most of the processing relies on manual labour. With the implementation of AI, analyzing and identifying patterns from a huge inflow of data becomes easier. This in turn is beneficial for brokers, agents and investors.

Commercial real estate data consists of various information ranging from rent roll, income statements, or mortgage history. An efficient customer relationship management tool organizes and manages such sensitive information of a client.

While manual processes pose the risk of data breaches and erroneous data entry, automation eliminates this concern and secures the privacy of renter information.

Moreover, an intuitive and centralized dashboard simplifies transaction management. The algorithms extract necessary data from the documents and formulate smart contracts which make transactions easier.

In addition to this, AI organizes massive data sets containing lease abstractions, legal and tax reports, property appraisal reports etc. AI-fueled classification of such data with useful metadata helps in the quick identification of the required information within large volumes of property documents. Hence, AI in commercial real estate integrates data management.

Steps towards AI implementation in a commercial real estate company

The commercial real estate industry as a sector has long been notoriously resistant towards a vision of digital transformation. 

However, for AI to be successful in reaping profits through analytics and automation, commercial real estate companies need an internal capability of company-wide strategy. Some of the steps to implement AI in commercial real estate are:

Benefits of AI in commercial real estate

The bottom line

It is evident that AI in commercial real estate is truly disruptive. With several of its algorithms that take care of property and data management to underwriting and market analysis, AI holds tremendous potential in transforming the commercial real estate industry operations and helping investors, brokers, lenders, agents and sellers to make data-driven decisions.