Artificial Intelligence is no longer a futuristic concept - it's reshaping how we analyze markets, serve clients, and make strategic decisions across global real estate portfolios. As the industry grapples with increasing data complexity and evolving client expectations, AI has emerged as the critical differentiator between market leaders and followers.

The CRE sector generates massive volumes of data daily through property transactions, market analytics, tenant behaviors, and economic indicators - making traditional processing methods obsolete. AI applications now include predictive analytics, automated valuations, portfolio optimization, and risk assessment, with machine learning analyzing satellite imagery, foot traffic, and ESG factors. According to several industry research, companies leveraging AI in real estate decision-making report 23% faster transaction times and 18% more accurate valuations compared to conventional approaches (1).

At JLL, we've systematically integrated AI solutions across our global operations, recognizing that AI isn't just about technology, it's about augmenting human expertise with data-driven insights. Our approach focuses on three core pillars: enhancing client advisory services, optimizing operational efficiency, and driving predictive market intelligence. JLL proprietary platforms now incorporate machine learning models that analyze thousands of market variables simultaneously, enabling us, professionals, to provide clients with unprecedented accuracy in strategic decision-making and market insights. The integration covers from JLL largest metropolitan markets to specialized regional operations, ensuring consistent service quality while supporting teams on a global level.

Building on this foundation of AI evolution, practical applications are already delivering measurable results across JLL's global portfolio. A compelling demonstration of this approach is Hank, an AI-powered HVAC optimization platform developed by JLL Technologies, that seamlessly integrates with existing Building Management Systems. Unlike traditional BMS that operate on fixed schedules and static parameters, Hank's algorithms continuously adapt to changing conditions, occupant needs, and equipment performance in real-time.

Hank combines machine learning, energy modeling, and external data sources to make intelligent micro-adjustments to building systems, creating a digital twin of the property to simulate and optimize operations. The system can anticipate building needs based on occupancy patterns and weather forecasts while identifying equipment anomalies before they lead to failures.

For instance, when implemented at Royal London's 12,500 sqm Birmingham property, the results were remarkable, delivering a 708% ROI with £148,000 (CHF 158,582) in guaranteed annual savings, a 21% reduction in energy consumption, a one-to-two-year extension of equipment life, and the prevention of 500 metric tons of carbon emissions annually (2).

These outcomes are a powerful demonstration of how smart building technology directly translates into measurable operational excellence and tangible asset value.

The success stories of AI applications such as the ones mentioned above highlight a crucial aspect of successful AI implementation: these tools deliver maximum value when integrated into comprehensive services guided by human expertise rather than deployed as standalone solutions.

Carbon Pathfinder - an advanced software that emerged as the winner of JLL's first hackathon in 2020-2021 - helps clients plan their decarbonization strategies across large real estate portfolios, exemplifies this synergy. The tool is built with the Carbon Risk Real Estate Monitor (CRREM) methodology (3), which provides emission factors for 20 countries, making it globally relevant - with a specific strength in European markets. This innovative tool is enabling the modeling of scenarios across entire real estate portfolios. It can visualize the impact of different strategies like “doing nothing”, pursuing a full LED lighting retrofit, or installing regional heat pumps, allowing it to quickly identify which assets to prioritize for deeper analysis.

While this powerful tool contains a huge amount of global data, it doesn't automatically understand the complex and specific regulations of every local market. Its real value is only unlocked when guided by an expert who can provide that crucial local context.

This is where a JLL professional steps in. Their job is to set practical goals for a property that aligns with local energy laws - a task that requires a deep and up-to-date understanding of these evolving standards. It’s a strategic role, not just a data-entry one. For instance, the expert uses their on-the-ground knowledge to decide if a solution the tool offers (e.g. installing new heat pumps) is even feasible for a unique building, such as a historic property with structural limitations. They also bring insight into financing opportunities to determine if a project is economically viable.

In essence, the expert uses Carbon Pathfinder not only as an “answer machine," but as a sophisticated calculator to test hypotheses grounded in real-world knowledge. This strategic integration of AI and human expertise offers tangible benefits, including accelerated decision-making, personalized strategies at scale, investment optimization, and robust long-term planning that future-proofs assets against tomorrow's challenges.