AI in Real Estate: 20 Examples to Know

Machine learning, which is one of the most common applications of AI, involves training machines with large amounts of data to recognize patterns, analyze data, and run forecasts and algorithms. In this look at AI in real estate, we’ll explore how the new technology is changing the real estate industry and some examples of AI in the real estate industry. 22 Please note that FINRA does not endorse or validate the use or effectiveness of any specific tools in fulfilling compliance obligations. FINRA encourages broker-dealers to conduct a comprehensive assessment of any compliance tools they wish to adopt to determine their benefits, implications and ability to meet their compliance needs. Artificial Intelligence (“AI”), or the simulation of human intelligence by machines, has been evolving for decades. Generative AI is the latest breakthrough category in the space, garnering attention for its ability to create original ideas and content.

How AI Transforms The Investment And Brokerage Business

For example, it can even alert individuals when updated records are due or proactively report on increased tenant demand, as an example. AI can also quickly classify, store, and resurface documents as needed, providing a glut of historical data to pull from and allowing property stakeholders to make more informed decisions. Increasing numbers of commercial real estate players are incorporating artificial intelligence into their marketing processes. AI is now being used to create highly targeted social media ads, listing copy, and even blog articles, taking much of the busywork out of human hands.

How Artificial Intelligence Is Changing the Real Estate Market

In the current scenario, some investment managers are suggesting that AI can be used for stock market forecasting but there are no specific AI driven tools that are widely being used by retail investors. In order to help investors make investment decisions, it is estimated that several brokerage platforms would provide users with an NLP based interface on their websites. We often think of U.S.-based manufacturing companies when it comes to new technologies like AI, but exposure to AI spans borders and industries.

The analyst will then be able to conduct a back‑and‑forth conversation with the LLM to refine the request. It unleashed a huge wave of interest in generative artificial intelligence (AI) and its possibilities. Leaders in virtually every industry across the globe are now evaluating how their businesses may be impacted by AI—and asset management is no exception. It creates 3D virtual tours of properties that allow potential buyers to explore a property using augmented reality and other features before going to visit in person. Visual representations have become increasingly important in real estate, and it’s one of a number of industries that are taking advantage of “digital twins,” or AI-based computer images that allow users to explore a space digitally. More broadly, artificial intelligence technology includes computer vision in industries like autonomous vehicles, as well as robotics, neural networks, voice recognition, and natural language processing.

The chart shows companies within the technology sector defined by BlackRock Systematic as having exposure to Artificial Intelligence technologies. This is for illustrative purposes only and is not meant to represent the past or future performance for the sector shown. Although AI has many upsides in the property industry, there are some potential downsides too. It is important to put the correct safeguards in place when dealing with any new technology and to act cautiously when appropriate.

Investment Processes

This has enabled investors to make informed decisions and maximize their returns on investment. Looking to the future, AI has tremendous potential to transform the commercial real estate industry even further. One area where AI is expected to have a significant impact is in the area of smart buildings.

This could include curated educational information, news, and research reports on specific investment products or asset classes. This content could be delivered to customers by email or directly through the firm’s website or mobile app. In addition, firms have also indicated AI tools are being explored to determine whether individuals would be interested in certain services based on their customer profile and browsing history within the firms’ websites. Hundreds of years of history shows us that investment bubbles have been a regularly occurring feature of the financial markets.

How AI Transforms The Investment And Brokerage Business

AI-powered solutions can analyze financial data, market data, and property data to identify investment opportunities, evaluate risk, and predict returns. This has the potential to revolutionize the way commercial real estate financing is done, enabling investors to make more informed decisions and access new sources of financing. AI has also transformed the way commercial real estate investors make investment decisions. AI-powered solutions can analyze market data, property data, and financial data to identify investment opportunities, evaluate risk, and forecast returns.

How AI Will Transform the Real Estate Market

At that same time, Nvidia, a leading AI developer, is close to becoming the sixth company worth $1 trillion. FINRA Data provides non-commercial use of data, specifically the ability to save data views and create and manage a Bond Watchlist. Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (“DTTL”), its global network of member firms, and their related entities (collectively, the “Deloitte organization”). DTTL (also referred to as “Deloitte Global”) and each of its member firms and related entities are legally separate and independent entities, which cannot obligate or bind each other in respect of third parties.

How AI Transforms The Investment And Brokerage Business

AI has also impacted the leasing process by automating various tasks that were traditionally performed by humans. AI-powered chatbots can assist tenants in their property search, answer frequently asked questions, and provide 24/7 customer support. This has reduced the workload of leasing agents and enabled them to focus on higher-value tasks such as negotiating lease terms and building relationships with tenants.

Led by Jordan Vinarub, our head of the TDC, we created a Data Insights Tech team with a mission to generate data, applications, and insights to support decision‑makers across the business. If you’re an investor looking for exposure to AI, consider looking at AI stocks or AI ETFs, or you can learn more about real estate investing to investigate more opportunities with AI in real estate. Forecasting is important, especially when investing in commercial real estate. Investors, agencies, and economists use AI to predict where the real estate market is headed, hoping to get an edge on the competition and buy at the right price. When you see an estimate on the value of a property, it’s generally based on predictive analytics from artificial intelligence. Even generative AI now plays a role in creating three-dimensional models of properties so that potential buyers can use any connected device, such as a smartphone or tablet, to get a sense of how they look.

  • It is also possible that a minority of bad landlords could use technology to limit the use of services, such as heating.
  • Firms may wish to review their AI-based investment tools to determine whether related activity may be deemed as offering discretionary investment advice and therefore implicate the Investment Advisors Act of 1940.
  • In some cases, AIs can also “hallucinate,” or confidently provide a generated response that is downright false and unjustified by any training data.
  • The fund may involve a greater degree of risk than an investment in other funds with greater diversification.

Some large firms have established centers of excellence to review, share, and build expertise and create synergies related to the use of AI across their organizations. In addition, firms are exploring and incorporating AI tools built by financial technology startups and vendors. In general, history shows that the greater and more rapid the investment in new technologies by businesses, the greater the potential impact on productivity. We can gauge the potential impact of AI by monitoring the scale of investment into AI-related capital focused on information processing equipment and software. We would expect a similar pattern as observed during the most recent, tech-driven boost to productivity in the 1990s internet boom. An upturn in technology investment by businesses took place around 1993, preceding the start of a rise in productivity just a few years later in 1996.

Secondly, AI is being used for making better recommendations about how to so business on brokerage platforms by analyzing individual investment and trading patterns. In conclusion, AI promises a transformation in the real estate broker model, making processes more efficient, informed, and proactive. However, it’s AI Trading in Brokerage essential to strike a balance between automation and the irreplaceable human touch that forms the foundation of the real estate business. The information provided here is for general informational purposes only and should not be considered an individualized recommendation or personalized investment advice.


Other issues to keep in mind are the customer authentication process, cybersecurity needs, and fair and accurate recordkeeping. They have industry knowledge and the ability to establish trustworthy relationships. AI will not be able to replicate their strategic thinking, negotiating abilities and unique approach, making them essential for navigating complex business transactions. Brokers who’ve spent many decades in the industry may recall when financials and underwriting calculations were all conducted manually.

According to one Deloitte study, only 1.3% of insurance companies are investing in AI. But according to Next Move Strategy Consulting, AI use is expected to grow twentyfold by 2030. This material is provided for informational purposes only and is not intended to be investment advice or a recommendation to take any particular investment action. In contending with the remote working environment compelled by the pandemic, innovation and collaboration were essential. The platform they created enabled our insights ecosystem to flourish through shared research, projects, and the continuous generation of thought leadership.

Yet these tools generally still require some oversight to make sure marketing materials come off precisely as intended and as best fit each use case. In some cases, AIs can also “hallucinate,” or confidently provide a generated response that is downright false and unjustified by any training data. On Crexi, our new AI Script feature allows brokers to upload an OM into a listing draft, and the software will automatically generate compelling, highly detailed marketing copy within seconds. Brokers no longer need to worry about the perfect marketing materials—computers can create them, and with minimal tweaks, they’ll do the trick and free up hours of copywriting and design time. That AI has improved by orders of magnitude unlocks the exponential capacity of models to transform many aspects of different businesses. For example, AI-generated 3D models allow prospective buyers to tour a property without leaving the comfort of their homes.

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