An Industry at a Crossroads

The real estate research field is currently undergoing a significant transformation. Historically, access to advanced data analysis was limited, but advancements in technology have democratized this domain. Today, anyone with a foundational understanding of data science can step into this arena. However, many established real estate investors and operators still rely on traditional organizational structures that hinder their ability to innovate.

Challenges Facing Traditional Structures

Typically, organizations place seasoned veterans—often lacking technical skills—in key supervisory roles, directing a small team of technically adept individuals without sufficient industry insight. This disconnect is a major barrier to effectively leveraging artificial intelligence (AI) in real estate research.

True advancements in AI are not merely about outsourcing analysis to algorithms but rather about enhancing the capabilities of experienced professionals. By 2025, it will be essential for these experts to have a solid grounding in technical data skills, enabling a collaborative relationship between human insight and machine learning capabilities.

Leveraging AI for Research Efficiency

AI offers the potential to streamline and enhance third-party real estate research and independent quantitative analytics. This advancement is likely to improve industry efficiency and profitability significantly.

Since 2020, progressive real estate firms have been integrating skilled data scientists who understand both the technology and the market. This integration has enabled some companies to reduce their research overhead drastically, with some firms reporting up to a two-thirds reduction in costs.

To illustrate the evolution of the industry, consider the case of Property and Portfolio Research, which had a substantial workforce dedicated to research operations before being acquired by CoStar in 2009. They have since managed all analysis with just a single individual, emphasizing the striking reduction in human resources available for research tasks, yet showcasing an increasing reliance on AI and data analytics.

Overcoming Communication Barriers

While AI excels at generating correlations from vast datasets, the interpretation and communication of these findings have historically constituted a bottleneck in the research process. Recently, AI technologies have begun to resolve these limitations effectively.

At Florey Street Advisors, for example, a suite of AI-driven tools is employed to articulate investment strategies in the multifamily sector dynamically. This framework allows human experts to integrate theoretical insights, model specifications, and comprehensive governance into their analyses. The system leverages data to fuel machine learning models, which subsequently inform analytical outputs presented through intuitive interfaces.

Envisioning the Future of Real Estate Research Teams

Looking ahead, the ideal real estate research team will be characterized by domain experts proficient in data analysis and machine learning. These professionals will focus on generating actionable insights, moving away from mere data dashboards or superficial analytical summaries.

In this new landscape, specialized AI agents will support the research process by effectively summarizing insights and recommendations. This will enable a more nuanced understanding of market conditions and investment strategies.

Moreover, AI will serve as a powerful content generation tool, helping sift through voluminous data to identify the most relevant information while improving the quality of research outputs.

Conclusion

The future of real estate research will increasingly depend on the intersection of domain expertise and data science skills. As AI becomes more integral to the research process, organizations that fail to adapt may find themselves at a disadvantage. The ability to engage with data directly and analyze it effectively will become a hallmark of successful real estate research teams, rendering traditional roles without technical acumen obsolete.