Artificial Intelligence's (AI) Impact on Commercial Real Estate

In this video Andrew is joined by Robin Rivaton, from Stonal, a data management platform for large asset owners and managers. The discussion highlights topics that are discussed in Stonal’s recent white paper covering various aspects of AI deployment, including machine learning, predictive models, and natural language interfaces. They also explore the challenges and opportunities associated with data quality, confidentiality, and the evolving landscape of the commercial real estate industry in the context of AI adoption. The following topics are discussed in this video:

• Stonal's Background: Robin provides insights into Stonal's role as a metadata management platform, detailing its focus on extracting information from documents and plans across various asset classes.
• AI in Commercial Real Estate: The discussion covers the use of AI in commercial real estate, with a focus on machine learning. Robin explains the significance of training models to perform tasks more efficiently than humans, highlighting applications such as document classification and metadata extraction.
• Predictive Models: The conversation explores the use of predictive models in commercial real estate, especially for valuation purposes. Robin discusses the potential of AI in predicting future trends, considering factors like prices, CapEx, and changes in building usage.
• Natural Language Interface: The video touches on the emerging trend of gaining access to data through natural language interfaces. Robin explains Stonal's work on developing its own large language model making data more accessible for decision-makers at various organizational levels.
• Acceleration of AI Usage: Andrew and Robin discuss the broader acceleration of AI usage in the commercial real estate sector, considering the challenges and opportunities presented by the industry's unique characteristics.
• Data Quality and Confidentiality: The conversation addresses the fundamental importance of good quality data in training and running AI models. Robin emphasizes the need for good datasets and discusses concerns around data confidentiality, with the reassuring message that responsible practices are being adopted across the industry.
• Risk Management: The discussion concludes with a focus on managing risks associated with data confidentiality, breaches, and the potential misuse of data. Both speakers highlight the importance of responsible AI deployment while encouraging the industry to embrace new technologies for future competitiveness.

Read the full white paper at https://stonal.com/en/white-paper-ai-real-estate/

More information regarding the Tech Partner Programme and our partner Stonal can be found at www.rics.org/techpartner