Jones Lang LaSalle leverages AI to transform real estate operations and sustainability
Jones Lang LaSalle (JLL), a global real estate services firm, is implementing AI-powered solutions to enhance operational efficiency, sustainability, and leasing management in commercial real estate. JLL uses Microsoft Azure AI solutions, including generative and agentic AI, for portfolio analytics, facility management, and investment optimization. The firm has adopted AI-driven PropTech to enable functions such as document standardization, facility automation using IoT data, price modeling for investments, and real-time customer engagement through chatbots. JLL’s solutions deliver actionable insights for investors, tenants, and property managers while enabling data-driven decision making across the portfolio. AI has also led to improved management of energy consumption in buildings, enabling ‘smart space’ utilization, and supporting the net-zero agenda. AI adoption by JLL has enabled more responsive, efficient, and sustainable property management, aligning with global trends toward decarbonization and green building standards. Key case studies cite energy savings of up to 59% and ROI improvements surpassing 700% by deploying AI-powered building management solutions. JLL’s systematic approach to AI integration includes piloting technology, implementing data quality protocols, and regulatory compliance regarding privacy and emissions reduction.
- Organization
- Jones Lang LaSalle
- Industry
- Real Estate
- Location
- United States
- Published
- March 2024
Reported outcomes
708%
quantified impactOther quantified impact
Strategic outcomes
Primary read
Use case focus
Showing 3 of 4
- 1AI-enabled facility management and energy optimization
- 2Automated tenant engagement with chatbots
- 3Investment modeling with generative AI
- JLL and its clients needed to improve efficiency and decision-making in commercial real estate management.
- Demand for sustainable, net-zero buildings required precise energy management and emissions reduction.
- Manual processes for analytics, leasing, and facility management were inefficient and labor-intensive.
- Tenant engagement and customer experience were limited by lack of personalized, AI-driven technology.
- Data volume and workflow complexities created obstacles for scalable digital transformation.
- Implemented Microsoft Azure AI for large-scale portfolio analytics and building management.
- Adopted generative and agentic AI for investment modeling and operational analysis.
- Used IoT data for automated, predictive facility maintenance and energy optimization.
- Deployed AI-enabled chatbots for tenant and customer interactions.
- Leveraged PropTech integration to standardize document processing and accelerate decision-making.
- Reduced building energy use by up to 59% and carbon emissions by 500 metric tons annually (UK case study).
- Achieved ROI up to 708% on AI-powered building management projects.
- Doubled the real estate footprint of AI companies in two years.
- Increased speed and accuracy of investment, leasing, and facility management decisions.
- Enhanced tenant engagement and experience.
Sources & evidence1
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