Artificial Intelligence (AI) has been transformative to the way many companies do business. In the health care sector, AI allows patients to easily access medical information. In the manufacturing industry, AI enables facilities to run more smoothly, optimizing the manufacturing process. In regards to retail, AI provides consumers with a more personalized shopping experience. Similarly, this rapidly developing technology promises to bring huge improvements in efficiency and accuracy to the entire functioning of the CRE industry.
Artificial Intelligence is not a new concept. The first discoveries of AI date back to 1955, but the technology that is currently in use has grown significantly since then. Simply put, AI as we know it today, refers to a class of algorithms that give computers the ability to “learn” from past data. In doing so, these algorithms can then be used to automate complex, often repetitive, tasks that previously could only be accomplished by humans. There are many different subfields within AI, each specialized to leverage a different type of data and solve a different set of problems
One subfield in particular, Natural Language Processing (NLP), has seen a tremendous amount of technological development in the past few years and, as a result, holds an abundance of untapped potential for companies interested in harnessing the power of AI to unlock opportunities and increase efficiency. Modern society produces more data in the form of text than in any other form, including pictures and video. Furthermore, text data, and the thousands of human languages that underlie it, is arguably one of the most complex types of widely available data. Therefore, in order to make use of text data, it is important for computers to be able to deal with its complexity and nuance. The recent developments in NLP have allowed AI to do just that. NLP is a field that gives machines the ability to parse, understand, and derive meaning from human language and text. Importantly, much of the data that CRE companies rely on consists of text data that is locked away in dense and lengthy lease documents. However, this data is only as good it’s ability to be easily accessed and understood.
One of the many and most useful NLP techniques that we at Prophia have begun to integrate in our product is Named Entity Recognition (NER). With NER, AI can automatically identify, classify, and extract words relating to the names of organizations, locations, measurements, and monetary values, among other things. At Prophia we are able to leverage a large private dataset consisting of hundreds of thousands of pages of lease documents to train state of the art NLP algorithms such as Google’s Bidirectional Encoder Representations from Transformers (BERT) to perform CRE specific NER.
What does all of this mean for our customers? In the past, the extraction of data from leases was done completely manually. Now, we are assisted by these technological advancements to significantly accelerate this process while maintaining the high level of data accuracy our customers expect. This allows our team to devote more time to one-on-one customer service and provide value to our customers much faster. As Yann LeCun, winner of the “Nobel Prize of Computing,” explains, “Our intelligence is what makes us human, and AI is an extension of that quality.”
The promise of AI is only just starting to be felt in a multitude of industries, including CRE. At Prophia we are dedicated to implementing AI technology into our approach to better help customers make the right decisions with the right information in the right amount of time.