Talk with Raphaël Cohen
Head of Data | Stonal
In an era where efficient data management is needed, AI emerges as a crucial asset. How is it implemented in real estate? What progress can we expect from it in the future? What tools is it based on? Raphaël Cohen, Head of AI / Data Science at Stonal, the European property operations Saas platform leader, explains.
Why do we need Artificial Intelligence in real estate?
AI has emerged as a valuable asset in the realm of efficient data management, playing a pivotal role in handling substantial volumes of documents. It enables efficient classification as well as extraction of information. Given that decisions in real estate often hinge upon comprehensive and precise data gleaned from diverse documents, the role of AI in this context becomes indispensable.
This adept data management, driven by AI, serves as a catalyst for well-informed decision-making. AI serves in data analysis for purposes such as cost optimisation, energy consumption, and benchmarking. These analytical capacities are crucial in advising clients on matters related to renovation and compliance.
Could you give us some examples of how AI is used in real estate nowadays?
AI’s applications manifest in various practical domains in real estate. First of all, AI plays a pivotal role in document processing by automating the extraction and classification of information from documents such as leases, contracts, and financial statements.
Additionally, AI contributes to operational efficiency by leveraging tools to analyse building performance, optimise costs (CapEx and OpEx), and energy consumption.
Furthermore, in the arena of renovation and compliance advising, AI models can predict the impact of renovations and help ensure compliance with regulations, aiding in decision-making processes.
What role does AI play within Stonal?
AI plays a crucial role within Stonal, especially in terms of document management. Our proprietary algorithms, only trained on real estate documents, categorize and extract key data from documents, streamlining workflow and improving accuracy in data handling and extraction. Among the documents concerned figure asbestos and lead surveys, energy performance or fire safety inspection certificates.
It is also of great help for benchmarking, using quantitative analysis. Stonal’s AI tools analyse building performance helping in optimizing costs, expenses, and energy consumption ; which is crucial for advising clients on renovation and compliance.
How does Stonal use artificial intelligence?
We deploy a diverse array of tools, each serving specific functions. Among these, Natural Language Processing (NLP) takes the forefront. Leveraging NLP algorithms, we empower our systems to comprehend and process human language embedded within documents. When language analysis is not sufficient, we use multimodal algorithms to take advantage of both language and visual information.
Additionally, we employ machine learning and predictive analytics to drive our quantitative analysis. Using statistical models, we can predict maintenance needs, optimize costs, and benchmark building performance, based on historical data and real-time inputs from multiple sources.
What is the uniqueness of Stonal regarding the use of AI and what can we expect in the future?
Stonal’s mission thrives on diversity, allowing us to tap into a vast array of industry data. This positions us uniquely to develop sophisticated, bespoke models and tools that precisely cater to our clients’ varied needs. We are working towards better data reconciliation, improving models by further merging and combining data sources (documents, floor plans, tabular…).
More generally, we will witness some enhancements in the industry. Moving beyond predictive analytics, AI will likely offer more diverse prescriptive solutions, suggesting optimal actions for cost savings, energy efficiency and compliance.
Download our white paper - AI's impact on CRE.
Want to know more about the impact of AI’s on commercial real estate? Download our White Paper and discover how AI will redefine strategies, elevate decision-making, and transform operational efficiency.