How AI Is Changing The Real Estate Industry

As we stand on the cusp of transformation in the commercial real estate industry, one cannot help but recall the sage words: "With great power comes great responsibility." In an era marked by technological advancements occurring at a blistering pace, the real estate industry (commercial, industrial, residential, office, hotel, and every other class of real estate) stands on the brink of transformation and the seemingly limitless promise and power of generative artificial intelligence (AI) looms large as both a disruptor and a savior. Just like virtually every other industry, the real estate industry is changing rapidly through the use of AI, and if you aren't adapting your business to account for those changes, you are putting your business at significant risk. Traditionally, change in the commercial real estate industry has been akin to an oil tanker making a 180-degree turn—slow, measured, laborious, and infrequent. The changes that have been brought upon by AI are more like making a 180-degree turn in a Ferrari— fast, loose, simple, and frequent. However, these competitive and rapid shifts, while alluring, come with increased risks and the need to proactively manage those risks. The questions on everyone's mind are: (i) Can AI really predict the future success of a project? (ii) How trustworthy is AI? (iii) How is AI going to change my business? and (iv) What do I need to be worried about?

Brokerage/Marketing/Investing

AI is already changing the brokerage sector, where AI-powered platforms are introducing new tools which promise to help brokers reshape the way properties are marketed and identified for clients. Beyond mere marketing prowess, AI algorithms also hold the potential to analyze investment criteria, matching investment opportunities, business plans, and risk tolerances, whether for conservative pension funds or risk-tolerant venture capitalists.

Underwriting/Due Diligence

The underwriting process, a cornerstone of commercial real estate investment and finance, also stands to benefit immensely from AI integration. By synthesizing multifaceted data points ranging from tenant and income information to environmental risks, AI holds the potential to minimize human error, enhancing the likelihood of sound underwriting and investment decisions. Simultaneously, comprehensive due diligence analysis, imperative for mitigating risks inherent in real estate transactions, can be foreseeably streamlined with AI-driven solutions. By automating reviews of critical documents from rent rolls, leases, and property contracts to title reports, surveys, and environmental reports, AI models will increasingly empower businesses and legal teams to navigate complex transactions with far greater speed and accuracy than ever before.

Regulatory Compliance

For entities subject to regulatory oversight, including REITs, banks, and other financial institutions, compliance is paramount, not to mention the bane of many a real estate professional's existence. AI offers a potential lifeline to compliance teams, streamlining the arduous task of monitoring and managing the intersection of real estate investment, ownership, and operation with governmental and quasi-governmental regulations. By automating compliance procedures, it is possible for AI to not only save time but also ensure adherence to regulatory frameworks, safeguarding against potential legal pitfalls.

Development/Management

Real estate developers stand to reap substantial benefits from AI's integration across the development lifecycle. Platforms are being developed that claim to provide real-time insights on design, cost, and constructability, empowering developers to optimize project feasibility and accelerate delivery timelines. Similarly, AI's potential extends beyond transactional phases to property and portfolio management, where automation promises to streamline tasks ranging from facilities management and collection of rent to financial reporting. By harnessing AI-driven automation, asset managers can look forward to optimized operational efficiency, enhanced tenant experiences, and greater returns on investment.

Transaction Documents and Closings

The documentation phase of real estate transactions and closing of real estate transactions are poised for a seismic shift as large compilations of data are harnessed to train generative AI engines (a frightening thought for some attorneys). By leveraging a company's historical deal data and written policy positions, it is foreseeable that AI will possess the sophistication to facilitate the drafting and negotiation of transaction documents with precise adherence to given parameters and with unprecedented efficiency and accuracy, and then quickly and efficiently to go through all of the necessary steps to proceed with a closing. However, companies need to be very careful about the use of historical data, as the ownership and use of such data has been subject to much scrutiny.1 The use of customer data in a manner that exceeds or otherwise is not permitted by the privacy policy in effect at the time the data was collected could be problematic. As companies think through these issues, some have (or will) update their Terms of Service (TOS) and/or privacy policy to address this.2 Before training any AI engines, an attorney should be consulted regarding the use of such data, as there have already been examples of companies spending millions on developing AI tools, only to have to unwind them when it has been discovered that the AI engines were trained on data that the companies didn't own. As discussed further below, no matter what the newest, shiniest AI platform promises, nothing can, nor should, replace the experience and judgment of seasoned business and legal professionals in reviewing, analyzing, scrutinizing, and correcting the work product of any AI platform.

Navigating Legal and Business Risks

While the potential benefits of AI in commercial real estate are vast, they are not without accompanying legal and business risks. As business and legal professionals embark on this transformative journey, it's imperative to tread carefully, mindful of the legal and ethical considerations inherent in AI adoption.

One of the foremost concerns surrounding AI adoption is security. With the digitization of sensitive data and the reliance on AI-driven analyses, the risk of data breaches and cyberattacks looms large. As commercial real estate transactions involve vast sums of money and highly confidential information, ensuring robust cybersecurity measures is paramount. Professionals must be fully informed of the terms and conditions of AI platforms they employ, both internally and externally. Moreover, they must invest in and develop secure systems and protocols to safeguard against potential threats, mitigate the risk of data breaches and inadvertent company information disclosures, and protect client confidentiality. Further, companies need to ensure that they have clear and unambiguous AI policies and procedures in place for their employees.3 These policies typically cover employee use of AI, open source issues with AI code generators, responsible development of AI technology and AI models, vendor use of AI in preparing company deliverables and other topics relevant to the company's involvement with AI.4 The draw of using public AI tools (like ChatGPT) to accomplish tasks quickly is strong, and employers without strict and clear policies in place with respect to the use of these tools can put their companies and their clients at significant risk.

Another critical consideration is the accuracy and reliability of AI-generated analyses. While AI platforms hold the promise of streamlining processes and providing valuable insights, their effectiveness is contingent upon the quality of the data they are trained on. Inaccurate or biased data can lead to flawed analyses, potentially resulting in costly errors and misinformed decisions. This is why it is imperative that companies understand the tools that are being used, how those tools have been developed, what information is being used to train those tools, and what information is being omitted from the training of those tools. As such, all attorneys and business professionals must exercise due diligence in vetting AI platforms and engines and validating their outputs, to ensure that the insights they provide are accurate, reliable, legally sound, and free from bias.

Additionally, the laws and regulations surrounding the use of AI are changing rapidly, and what is in compliance with law today may be prohibited tomorrow.

Build Versus Buy

Whether you use third-party AI tools, fine tune third-party models, or build your own AI tools, there are unique legal issues to consider. For example, if you use third-party tools, you may still be liable for any issues with the output (e.g., inaccuracy, bias, infringement, or illegal activity). To manage these risks, it is important to conduct AI-focused vendor diligence. This includes considerations beyond the traditional vendor diligence that companies conduct when adopting third-party technology. If you fine tune third-party models or build your own AI, you need to ensure that you have development policies that will minimize legal risks. This includes ensuring the right to use the training data, ensuring legal compliance, and employing responsible AI development processes.⁵

How to Get Started

The range of legal issues with AI and the need to manage those risks may seem daunting, but there is a proven process to tackle these issues. Companies looking to adopt AI should take the following steps. First, develop an AI governance committee. This should include representatives from different parts of the company to ensure relevant stakeholders are included. Next, it is critical that the committee members receive sufficient training to understand the legal issues. It is difficult to make informed decisions without this understanding. Due to the rapidly changing legal landscape, ongoing training is necessary. Then, the committee should develop the AI policies based on the role the company will play with AI (e.g., build versus buy, etc.).⁶ Development of AI policies and procedures is crucial to the safe use of AI and the mitigation of risk.

Footnotes

1. See James Gatto, FTC Warns About Changing Terms of Service or Privacy Policy to Train AI on Previously Collected Data, Sheppard Mullin (Mar. 1, 2024), https://www.ailawandpolicy.com/2024/03/ftc-warns-about-changing-terms-of-service-or-privacy-policyto-train-ai-on-previously-collected-data/.

2. Id.

3. James Gatto, Why Companies Need AI Legal Training and Must Develop AI Policies, Sheppard Mullin (May 2024), https://www. ailawandpolicy.com/wp-content/uploads/sites/65/2024/05/Why-Companies-Need-AI-Legal-Training-and-Must-Develop-AIPolicies.pdf.

4. Id.

5. See James Gatto, Responsible AI – Everyone is Talking About it But What Is It?, Sheppard Mullin (May 3, 2024),https://www. ailawandpolicy.com/category/responsible-ai/.

6. See Gatto, Why Companies Need AI Legal Training and Must Develop AI Policies, supra note 3.