.svg){kind=icon}
In recent years, Artificial Intelligence (AI) in real estate development has emerged as a force to improve processes and enhance decision-making. We recently sat down with Will O'Donnell, Managing Director and Founder at Prologis Ventures to talk about the current and future role of AI in real estate development. He articulates this transformation, stating, “AI unlocks the ability to connect the dots across data sets that we never would've thought possible.”
In fact, AI isn’t new. It’s been around for years and it’s becoming more prominent recently because of large language models democratizing its use in the general public. In real estate development, companies have been investing in AI to drive their business forward.
JLL’s 2023 Global Real Estate Technology Survey reports that AI and generative AI were ranked among the top 3 technologies that were expected to have the greatest impact on real estate over the next three years.
Let’s delve into the current landscape, the return on investment, the strategies for adoption, and the potential future developments of AI in real estate.
The Current Role of AI in Real Estate Development
AI has seamlessly integrated into various facets of real estate development, from accelerating data analysis to maximizing design options and reducing cost.
Data Analysis
Historically, processing data is a huge bottleneck in the real estate development process. On average, data scientists spend about 60% of their time cleaning up data into a workable format.
In real estate development, where data scientists are not prevalent, we rely on architects and developers to process all this data before they can even start laying buildings on a site. But with AI, the deal team can process and analyze data at remarkable speeds, accelerating the data analysis process in site planning.
For example, if you’re doing an environmental review, historically you had to read through thousands of pages of documents to understand the regulations. AI allows that documentation to be digitalized and summarized into very clear takeaways.
Some AI tools, like TestFit, also have built-in ESRI datasets like parcel data and site constraints (easements, wetlands, flood maps, etc.) so the deal teams can easily strategize their planning from the very beginning.
“Over the years, we have been in situations where we run into zoning restrictions or entitlement issues. And rather than spending 2–3 months to discover a problem, I can discover it in 10 minutes with AI, allowing people to make better decisions earlier.”
—Will O'Donnell, Managing Director and Founder at Prologis Ventures
Design and Planning Iterations
AI is a powerful tool for optimizing building designs and maximizing site utilization. Design options for conceptual/design development ranked first as the greatest long-term potential use of AI among architecture firms.
Design iterations often take up a big chunk of time and fees early on in the design process, leaving the deal team rushing to deliver a final project at the end. But what if we flip the script and reduce the time spent on iterations while increasing the number of iterations we can explore?
On average, customers are generating 2-3x more design iterations using TestFit real-time AI, while saving over 9+ hours per feasibility study. This allows people to get back to doing what they love—being creative in finding solutions and maximizing the value of the land instead of dwelling in the tediousness of drawing parking stalls.
“With TestFit, we could immediately try out different scenarios…(and) see in real time what the implications are. Instead of spending time waiting and passing information back and forth, you can all get on the same screen and creatively think and run through 20, 30 different scenarios and in real-time see the value and benefits of each.”
—Will O'Donnell, Managing Director and Founder at Prologis Ventures
Cost Estimation
Traditionally, nearly 50% of contractors wait until the design development phase or construction document phase to get involved in preconstruction. This delays the process of cost estimation until it’s too late.
To minimize the potential risk of a deal, development companies can now use AI to estimate conceptual costs in the feasibility study phase. This allows them to allocate resources efficiently, and significantly save costs in change orders down the line. “Now we can use a tool like TestFit and combine it with our proprietary costing data. Suddenly, we can get insights that we didn't even know would be possible two years ago,” O'Donnell stated.
Adopting AI in Real Estate
Embracing AI in real estate requires a holistic approach among organizations, fostering a culture of data-centricity, diversity, and continuous learning.
Building a Data-Centric Culture
According to an IBM report, poor data quality costs the U.S. economy around $3.1 trillion per year. Inadequate data management has huge financial implications, especially when enhancing the accuracy and reliability of AI’s output.
You can’t succeed with AI without correct data. If we’re not entering correct data, we will only get incorrect results, no matter how advanced of an AI tool we use. “Being data-centric is a commitment and needs to be very intentional,” O'Donnell asserts.
Bringing in Diverse Perspectives
Diversity brings different perspectives and ideas, and it’s crucial for the success of AI in our industry. “If I have 20 people in the room who've been doing the exact same job for 20 years, you kind of know the answer. But if you can bring in diverse perspectives, you’re hiring the best talent that allows you to see things differently,” O'Donnell emphasizes.
On top of that, companies need to create an inclusive culture that allows their team members to ask questions and act with autonomy. Laura Paciano, SVP of Growth at TestFit, highlighted our entrepreneurial culture in an interview with Built In, “At TestFit, we set the vision for where the company is going and then quickly move the authority to where the information is. This creates an environment for thinking rather than following orders.”
Learning from Adjacent Industries
The rapidly evolving field of AI requires a commitment to continuous learning and development, even from adjacent fields. Just because something hasn’t been done in real estate, we can look at other industries and see how they have been using AI.
For example, in healthcare, AI-powered image recognition is used to analyze medical images like X-rays and MRIs to detect abnormalities and assist in diagnosis. In a similar way, Prologis is using AI for roof and paving inspections. Instead of having people walk on the roofs and take photos, they can now have AI process drone imagery to predict failure and plan maintenance way ahead of time.
Companies have to stay intellectually curious and challenge existing norms especially when we know these norms are rapidly changing with AI technology. This is why focusing on data, inviting in a diverse perspective, and learning from adjacent industries can help everyone in your organization to stay competitive.
The Future of AI in Real Estate Development
AI is set to play an even more significant role in shaping the future of real estate development.
Enhanced Collaboration
The building industry is a collaborative effort. It takes a large team of developers, architects, contractors, and consultants to construct a building. While currently each stakeholder work in silos, we believe that AI can help foster stronger collaboration between each discipline.
New TestFit research shows that 75% of developers agree that TestFit’s real-time AI has improved their internal communications and collaboration between teams. And 67% found it improved their external relationships with consultants and contractors. By removing people from the mundane work, the deal team can focus on sharing ideas with accurate data and insights in real time.
The transparency in data within AI also helps improve relationships in our larger community. Our customer, Cascadia Partners, finds that TestFit reduces suspicions and builds trust between city planners and developers by involving development data in conversations.
Faster Decision-Making
The integration of AI in real estate development is set to significantly expedite decision-making processes. With the capability to analyze vast amounts of data at an unprecedented speed, AI can provide developers and architects with real-time insights into design, cost, and constructability.
Furthermore, an AI-driven real estate feasibility platform can evaluate the feasibility of proposed deals, taking into account various factors such as location, zoning laws, and site constraints. By automating these complex analyses, AI enables quicker, more informed decisions, ultimately leading to more successful and profitable development projects.
“It's part of a big reason we’re so excited about TestFit. It's going to enable our construction and development teams to spend more time on strategic outputs and driving value and be able to make faster, better decisions.”
—Will O'Donnell, Managing Director and Founder at Prologis Ventures
Customization with AI
While AI tools like TestFit can generate multiple design iterations in seconds, we still need the human touch to customize it for each situation. This is vital, especially in real estate development where the expertise of developers and architects can make or break a deal.
Real estate development firm Resia uses TestFit to customize its building models like importing its configuration and standards without compromising its existing unit standards. As Clifton Harness, CEO and Co-Founder at TestFit describes, “The key that makes TestFit different is that our users can generate it and they can reach in, edit, and manipulate to make it better.”
It’s Time to Get AI-Ready
AI is not a futuristic concept anymore; it is here, and it is making a tangible impact. The current role of AI in real estate development is just scratching the surface. By breaking down data silos, enhancing collaboration across teams, and enabling faster decision-making, AI is positioning itself as an indispensable tool for the future of the industry.
The ability to generate rapid design iterations and obtain cost estimations early in the development process is revolutionizing the way developers, architects, and stakeholders approach deals, saving invaluable time and resources.
To get a deeper understanding of how companies leverage AI to drive revenue in their real estate development process, download the 2023 TestFit ROI report here.
