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How AI is changing the real estate market – TechTarget

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AI adoption is booming across all sectors, and the real estate industry is no exception.

The market for AI in real estate was valued at $164.96 billion in 2023, with projections hitting $226.71 billion by the end of 2024 and $731.59 billion by 2028, according to a January 2024 market intelligence report. Machine learning, natural language processing and computer vision are the most widely used AI technologies in the sector, the report noted.


Buy/sell, rent/lease residential &
commercials real estate properties.

In addition, research by Delta Media Group found that 75% of surveyed U.S. real estate brokerages have adopted AI. The survey, also released in January, found that 82% of surveyed agents used AI to craft property descriptions. Two-thirds of those agents used it to generate blog posts, emails and letters; 60% to create social media content; and 44% to create website content.

As industry practitioners find new ways to incorporate AI into their work, more opportunities surface for AI in the real estate industry. Here’s a look at seven of the most prominent use cases, as well as challenges to look out for.

1. Document review and summarization

Many real estate professionals, particularly in commercial real estate, use AI for document review. AI tools can process numerous pages of legalese to produce summaries and insights that would be too cumbersome to routinely handle manually.

John D’Angelo, who leads the U.S. real estate industry sector at Deloitte Consulting, pointed to AI’s use in lease abstraction. AI tools can review and summarize leases and highlight key provisions, enabling property owners, real estate professionals and leaseholders to perform this task quickly, accurately and at scale. This AI application is particularly helpful to professionals who need to gain insights into dozens or even hundreds of leases, D’Angelo said.

“[AI] technology takes away laborious work and gets the machine to work for you. It’s also making the impracticable both possible and practical,” he said.

2. Financial evaluations

AI tools can provide precise information about current asset values, predict likely future values and offer accurate recommendations on actions to take. Moreover, AI can deliver this information in real time, said Dan Weisman, director of innovation strategy within the strategic business, innovation and technology group at the National Association of Realtors.

“AI-type technology has been used for years to perform property valuations and appraisals,” Weisman said. “Now we have more data available, so we can actually do more with it and also have more accuracy and transparency.” For example, investors could use AI to determine the optimal markets in which to invest or when to broker a deal.

AI also helps remove human assumptions from valuations, Weisman added, leading to better decision-making — though it’s important to keep in mind that AI can also reflect and perpetuate human biases.

3. Property maintenance and management

AI aids commercial real estate owners and managers in maintaining their properties by using data from various sources — such as endpoint sensors, IoT devices and weather reports — to understand patterns, trends and needs, Weisman said.

For example, some companies use AI to analyze human movement within buildings such as airports and malls to gain insights into buying patterns. Those insights can then inform better building designs that are more responsive to purchaser needs, enhancing the overall user experience.

4. Sustainability and efficiency efforts

AI has already been instrumental in creating more efficient and environmentally sustainable buildings, said Tyler Wiggers, assistant lecturer and director of industry partners and engagement at the Center for Real Estate Finance and Investment at Miami University’s Farmer School of Business.

AI-powered building management systems gather data from multiple sources, such as IoT devices, weather reports and HVAC units, to analyze and predict energy needs and adjust accordingly. These systems proactively optimize and dynamically manage energy consumption, minimizing waste.

And it’s not only commercial real estate that benefits from AI in this way, Weisman added. AI-powered smart homes can understand residents’ needs and patterns, enabling them to manage their homes more effectively.

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5. Enhanced security

Real estate owners and managers can also use AI tools, such as computer vision systems with automatic alerting functions, in their security operations.

AI can analyze activity and detect movements — or even indicators of mood — more effectively than the human eye or a simple camera system, Wiggers said.

6. Visualization

AI-powered tools can create virtual representations of spaces, helping architects, builders and designers visualize realistic versions of envisioned projects throughout the design and construction phases, D’Angelo said.

AI also enables people to interact with and modify spaces digitally, whether on a computer screen or through augmented and virtual reality headsets.

“[AI] can generate a rendering of a space that someone can walk through before that space gets built, and it can simulate how people will interact in that space,” D’Angelo said.

7. Planning and development

AI can quickly comb through large amounts of data to identify patterns that humans cannot, making it an essential tool for property owners and operators seeking to understand future trends, D’Angelo said. For example, AI can analyze current weather patterns and geographic data to predict future scenarios and identify whether real estate assets could be threatened by climate change.

In addition, owners and managers of retail complexes can use AI to determine optimal tenant mix, helping tenants maximize sales and enabling facility owners to charge higher rents, Wiggers said.

“The power of AI can go through so much data and do it so quickly that it’s able to make correlations that you’d never be able to discover [without the technology],” Wiggers explained.

AI can also predict real estate supply-and-demand trends in certain regions over specific periods of time, he said. This capability lets planners and developers more effectively balance real estate supply and demand.

“The mismatch [between supply and demand] won’t completely go away, but AI will help minimize it,” Wiggers said.

AI challenges in real estate and mitigation strategies

Although AI use is on the upswing among real estate entities, the industry has yet to see transformative changes, D’Angelo said. Similar to many other industries, the real estate sector faces challenges in using AI for both incremental improvements and transformative use cases.

One of the biggest hurdles is readying the data required to fuel AI systems, he said. Other major challenges include planning and prioritizing projects, as well as identifying and mitigating risks like algorithmic bias and security concerns.

For example, algorithmic bias can occur when AI tools and systems are trained on internet data and learn certain biases and stereotypes affecting marginalized communities. In the context of real estate, AI bias could perpetuate housing discrimination, among other concerns.

To mitigate such risks and account for the limitations of AI tools, real estate practitioners must assign human evaluators to check the output of AI systems when making decisions, predictions and suggestions.

Mary K. Pratt is an award-winning freelance journalist with a focus on covering enterprise IT and cybersecurity management.

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