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How Large Language Models Unlock Data Connections and Efficiency

October 2, 2024 5 mins

This 5-part blog series created by LightBox is part of its Data and Technology Program partnership with CREW Network. Given its broad breadth across key segments of CRE, LightBox is in a unique position to report on the trends taking root and how today’s CRE professionals are responding to them. These five trends are reshaping the landscape of our industry and unlocking myriad avenues for professionals to be more efficient, make smarter decisions, and reduce redundancy in their day-to-day operations.

The universe of data on commercial properties is growing at breakneck speed, along with new ways to access, analyze and connect previously disparate datasets. Innovative applications are surfacing across CRE as professionals get better at understanding and using Large Language Models (LLMs) like ChatGPT to extract, interpret, and correlate vast amounts of data often buried within large documents and databases. Although machine learning applications for automating myriad labor-intensive functions in CRE have been around for some time, the emergence and rapid adoption of AI and ChatGPT are more recent.

Large Language Models 101

While the term LLM may not be in your everyday vocabulary, you are likely interacting with this technology daily, and it is poised to offer valuable benefits for your business. At their core, LLMs are types of machine learning models designed to process and generate human-like text based on massive datasets. Trained on billions of words, these models learn to understand and predict patterns in language, enabling them to answer questions, write text, summarize content, and even perform more complex tasks like identifying trends or predicting outcomes.

LLMs work by breaking down language into tokens (small units like words or phrases) and learning the relationships between them, giving them an understanding of patterns in language, which helps them create clear and relevant responses based on several types of input. This capability has made LLMs invaluable tools in industries that rely heavily on processing vast amounts of information, such as CRE.

One of the most significant advantages of LLMs is their ability to handle unstructured data—data that does not neatly fit into rows and columns. In the CRE industry, this means LLMs can extract useful insights from contracts, leases, meeting transcripts, and property reports that would otherwise require hours of manual review. By automating these processes, LLMs are helping professionals unlock new efficiencies in how they handle and interpret large volumes of data.

Eric Bollens
Chief Technology Officer LightBox

“While the surge in AI developments is a relatively new phenomenon, machine learning is not new to LightBox. We have been leveraging it within our products for over half a decade. For instance, a subset of our building footprints in SmartFabric are generated from image recognition neural networks being applied over aerial imagery, our LightBox geocoder leverages a variety of natural language processing and decision-making models in order to resolve queries more accurately than traditional geocoders, and our location and environmental data ingestion processes rely on a series of machine learning models for normalization, linking and conflation.”

LLMs in CRE Are Still in Their Infancy

Although many CRE professionals are still in the initial stages of embracing AI, the use of LLMs is gaining momentum. CREW Network’s 2024 industry research paper, Leveraging AI as a Business Advantage, draws on survey data from more than 1,000 CRE professionals to explore how CRE companies are using AI. The survey found that when it comes to knowledge of AI, 52% of CRE professionals know very little to nothing about it, and 38% of commercial real estate professionals have never used Al at work—only 11% use it daily on the job. This indicates a significant opportunity for growth, as AI has the potential to transform daily operations, streamline decision-making, and provide a competitive edge. Over time, as education and awareness expand, the CRE industry will more broadly harness and apply AI capabilities.

The potential for LLMs in CRE extends beyond simple automation; they are being used to summarize long documents, identify trends, and predict market outcomes—transforming how data is interpreted and utilized in decision-making.

The Pace of Change is Quickening: Jump in Now!

As LLMs evolve and new models evolve and continue to rapidly advance, the pace of AI adoption in the CRE sector is poised to accelerate. CRE professionals are discovering new ways to leverage AI for quickly analyzing data, trend identification, summarizing long documents or meetings, predicting outcomes, targeted marketing, report generation, and more. The rapid development of AI technology, as Bollens highlighted, has seen “new models leapfrogging everything that came before, almost quarterly.” This breakneck speed of development presents both excitement and challenges, as staying prepared for the ever-evolving AI landscape requires continuous learning and adaptation.

For those unfamiliar with AI, learning how to use and apply it may seem like a truly daunting task. Bollens stressed the importance of fearlessly taking the first step: “AI is one of those things you learn by doing. If you haven’t jumped in yet, sign up for one of the many free models and give it a shot. Start by asking it to write you an outline for a presentation or an email.”

As AI continues to reshape CRE workflows, those combining the power of generative AI with domain knowledge will be at the forefront of innovation. When you’re ready to take that step, “LightBox AI offers tools to bridge that gap and enhance your CRE operations,” Bollens said.

With our broad reach and unique insights, we are well positioned to track and report on the leading trends that are shaping the CRE industry today. Stay tuned to this page, where we will continue to highlight these trends and provide deeper analysis on how they are impacting the future of CRE.

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