From Data to AI: Don’t put the cart in front of the horse

In the world of real estate, Artificial Intelligence (AI) promises remarkable possibilities: predictive analytics, automated workflows, and intelligent decision-making. But before a business can harness the full potential of AI, it must first address a foundational challenge: managing data. In other words, one cannot put the cart in front of the horse. AI without clean, centralized, and trustworthy data is but a pipedream.

There is a set of steps that need to be followed to get to accurate, useful AI:

Centralize and normalize: The first step is to extract data from the various systems that real estate companies rely on—property management platforms, leasing systems, tenant communication tools, and even financial software. These systems often operate in silos, making it difficult to get a holistic view of the business. Bringing this data together into a central repository is critical. This process, often called ETL (extract, transform, load), ensures that all relevant information is accessible for analysis. Without it, AI initiatives will simply operate on fragmented or incomplete information.

Quality assurance: Once the data is centralized, it is paramount to ensure its quality and trustworthiness. Real estate companies must address duplicate records, missing data, or inaccurate entries. Data governance practices, such as regular audits and validation, are essential to build a strong foundation. Only when this foundation is in place can AI initiatives truly deliver results.

A.I can start: AI's first role is in helping businesses understand their data better. AI can identify patterns, create new metrics, and highlight previously unseen trends, such as tenant behavior or market fluctuations. These insights can transform decision-making, giving real estate professionals a clearer picture of their portfolio’s performance.

A.I can fly: Finally, AI can be used to automate workflows, driving efficiency and reducing manual work. Automated lease renewals, predictive maintenance, and intelligent tenant screening are just a few examples of where AI can transform daily operations. However, these efficiencies are only possible once the underlying data is correct and reliable.

In conclusion, the journey from data to AI in the real estate industry is a process that must be carefully managed. Businesses can lay the groundwork for successful AI adoption by first focusing on consolidating and validating data. AI is not just a tool for insight but a powerful force for automation—once the proper steps are taken to ensure that the data driving it is robust.

UDP's role in this journey

UDP is an end-to-end data platform, bringing the data together in one place, normalizing it, quality-assuring it, and allowing it to be represented as desired for reporting and monitoring use cases. It is also a source of truth for machine learning and A.I models that run on top of UDP.