Hello, I hold a PhD in Real Estate, lead MTSU’s Real Estate Studies program in our Economics and Finance Department, and am a faculty affiliate in MTSU’s Data Science Institute. Today, I want to share with you an intriguing experiment I conducted recently, where I harnessed the capabilities of AI to analyze a real-life real estate investment opportunity. What I discovered left me both impressed and hopeful about the evolving role of AI in the real estate industry.

A Real-Life Investment Scenario

As someone deeply involved in data science and real estate, I’m no stranger to complex financial analyses and investment strategies. When a real-world investment opportunity came my way, I saw it as the perfect chance to put AI to the test.

This investment opportunity came complete with specific details:

• Property Information: This included essential data such as the purchase price, initial rent, rental growth rate, property growth rate, insurance, maintenance costs, and a range of other financial inputs.
• Loan Information: I had access to key loan details like the loan-to-value ratio, loan amount, interest rate, loan term, and payments per year.
• Tax and Expense Data: This encompassed marginal tax rates, property tax percentages, selling expenses, and more.

Armed with these details, I embarked on an experiment that would ultimately highlight the potential of AI in real estate analysis.

The AI’s Role in My Analysis

In this experiment, I used a powerful language model known as ChatGPT to analyze the investment opportunity. While AI models like ChatGPT aren’t specifically designed for financial modeling, they are incredibly versatile and adept at working with complex data.

I fed the AI with the details of the investment opportunity and posed critical questions about the feasibility of buying and owning the property compared to renting it. I also asked for insights into potential tax benefits and anticipated cash flows over the years.

Impressions of the AI’s Capabilities

As someone who has spent years studying real estate and financial analysis, I approached the AI’s recommendations with a discerning eye. What I found was genuinely impressive. Despite not being a specialized financial tool, the AI demonstrated an uncanny ability to navigate the intricacies of the investment proforma.

The AI accurately computed the annual debt service, equity investment, and even provided a summary loan schedule. It projected property values and rental income over several years, helping me visualize the long-term potential of the investment. The AI also offered insights into tax deductions, tax savings, and the net costs of owning versus renting.

Perhaps most importantly, it calculated after-tax cash flows and assessed the profitability of the investment over time. What truly amazed me was that the AI’s recommendations were in sync with my own expertise and intuition as a seasoned real estate professional. It identified the initial cost of owning versus renting and, crucially, showed that over time, the investment was projected to become financially advantageous. The AI’s After-Tax Internal Rate of Return (ATIRR) calculations mirrored my understanding of the potential returns.

The Impact on Real Estate Certification

Now, let’s consider the bigger picture: AI’s role in real estate investment and its potential impact on certifications like CCIMs (Certified Commercial Investment Members). These certifications have long been revered in the industry, signifying expertise in commercial real estate analysis and investment.

As a long-time real estate investor myself, I’ve seen the value and prestige these certifications bring to the table. However, as AI continues to evolve and become more accessible, it raises intriguing questions about their role in decision-making.

Traditionally, CCIMs and similar certifications have been sought after for their ability to provide expert guidance in real estate investment. But what happens when access to AI becomes widespread, allowing individuals to harness the analytical power of machines? Could AI-assisted analysis provide even more accurate and data-driven insights? And importantly, could it do so without any vested interests or commissions, delivering truly unbiased advice?

These are questions that the industry may need to grapple with in the coming years. While certifications like CCIM will always hold value in terms of their comprehensive knowledge and experience, AI presents a unique opportunity to complement and enhance these qualifications.

In conclusion, my real-life experiment demonstrates the power of AI in the realm of real estate investment. As a professor and a Ph.D. holder, my endorsement of the AI’s results carries weight, and I believe it’s an exciting development. As AI continues to advance, it will be fascinating to see how it integrates into the everyday practices of real estate professionals and investors. The future of real estate investment is looking more data-driven than ever before, and this may well redefine the roles of industry certifications in the years to come.

Dr. Philip Seagraves, Director of Real Estate Studies and Faculty Affiliate in Data Science