JLL unveils AI assistant to boost property portfolio insights
JLL has introduced a new artificial intelligence solution designed for owners of retail, industrial and office properties.
The solution, named JLL Property Assistant, is powered by JLL Falcon and is intended to provide property and asset managers with quicker access to data-driven insights, aiming to enhance the performance of property portfolios. The tool allows users to engage directly with portfolio data using natural language questions, such as "Which retail assets have the highest vacancy risks in Q3?", offering immediate and comprehensive responses.
According to JLL, the Property Assistant can generate detailed tenancy reports and stacking plans, as well as analyse expense trends over time. The platform helps reveal important data on tenant retention and occupancy patterns. It also breaks down operational budgets, highlights opportunities for cost control, and offers suggestions to fill vacancies with the aim of maximising rental income.
JLL Property Assistant works within a conversational interface and integrates with JLL's Acumen platform, which brings together financial data from systems like Yardi and MRI, operational data from Prism by Building Engines, and other property technology tools. This integration consolidates information into a unified platform, providing property managers with a single source for performance data and reducing the inefficiencies caused by data silos.
Neil Murray, Chief Executive Officer of Real Estate Management Services at JLL, said: "JLL Property Assistant will help our clients unlock the true potential of artificial intelligence for the real estate they own. Built on JLL Falcon, the tool provides a unique, interconnected experience that streamlines operations, enhances decision-making, and drives unparalleled value creation. These components - AI, data and best-in-class applications - form the foundation of JLL's property management technology platform, a one-of-a-kind, unified software suite purpose-built to advance the performance and returns of our clients' properties."
Users of JLL Property Assistant can ask for portfolio summaries such as net operating income year-to-date, and receive prompt, data-driven answers. The system is designed to let property professionals focus on strategic activities by dramatically reducing the time spent searching for information.
The AI assistant's functionality extends to creating comprehensive tenancy reports and stacking plans automatically, tracking and analysing expense patterns, and identifying opportunities through earlier detection of emerging trends in tenant retention and occupancy. This advanced reporting is intended to support a more proactive approach to portfolio management.
The operational aspect of the platform includes tools for real-time monitoring of high-priority tasks, identification of possible tenant satisfaction issues, and analysis of maintenance work order trends. These features are designed to reduce operational costs and improve both tenant retention and experience.
Financial management is another focus area for the Property Assistant. Through the delivery of detailed operational budget breakdowns and targeted recommendations for cost control, the solution aims to streamline finance reporting, freeing up managers to focus on value-adding activities. The tool also provides data-driven suggestions for filling vacancies in order to increase rental income.
Yao Morin, Chief Technology Officer at JLL, commented: "Our AI-powered assistant fundamentally transforms the management of property for investors, delivering unprecedented efficiency, data-driven insights, and optimised performance. The tool empowers property managers and owners to focus on strategic initiatives and enhanced property performance, ultimately driving greater value for their portfolios and revolutionising the industry."
JLL has stated that security and privacy were key priorities in the development of the platform. JLL Property Assistant uses enterprise-grade security protocols and applies anonymised global benchmarks for industry analysis. This is intended to ensure the protection of client data while still permitting comparative analytics across the sector.
