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.

The remarkable technological transformation CRE has undergone over the past three decades, has established the foundation for today's AI revolution. This evolution represents not merely incremental improvement, but a fundamental shift in how the industry approaches data analysis and decision-making.

This advancement addresses a historical challenge that has long plagued the real estate industry. CRE has traditionally suffered from relatively low data transparency compared to other industries, which severely limited the ability to conduct predictive modelling. The traditional approach required manual data collection through staff members to manually gather and structure information, a process that was not only time-intensive but also prone to errors with limited visibility into quality issues. AI represents a fundamental shift from this manual - subjective approach, to an objective - data-driven methodology.

As Phoebe Holtzman - Global Director of Data Science Innovation at JLL - explains, the most significant transformation has been what she calls a "data generation revolution." Her team, which focuses on using predictive modeling to better understand real estate markets, can now create structured data from previously unstructured sources. "We can now take data from documents, we can generate data from Street View or satellite images and create really clear structured data sets - which was very difficult to do in the past," she states. This ability to generate significantly more data enables substantially more sophisticated predictive modeling, representing one of the most profound impacts the industry has experienced.

A powerful application of this is a model that Phoebe’s team developed to identify features that contribute most to a building's value, including: amenities, lobby quality, elevators, and ceiling heights. However, one crucial element was always difficult to measure: facade quality. "We know, being in real estate, that when you walk up to a building, if the facade is falling apart, you will have a different reaction than if it's a beautiful or historical facade that is well maintained." By using AI to extract facade quality information from Google Street View imagery, her team can now generate objective quality metrics for buildings at scale, a task that would have been prohibitively expensive and time-consuming with manual labor. This new approach has, in her words, "profoundly sped things up". While reliability varies by market, Phoebe’s team is expanding this capability globally. The beauty of AI-powered solutions, according to her, lies in their scalability. "Once we've built it out in a sufficient number of markets that we feel confident in the performance, then we can bring it anywhere."

Although very specialized markets like Switzerland still face adaptation challenges, AI's scalability offers tremendous advantages for markets of all sizes. The beauty of AI-powered solutions lies in their potential for global deployment—once built and validated across major markets like New York, Paris, London, Sydney, Tokyo, and Hong Kong, these models can be brought to smaller markets without the previous constraints of requiring local staff to manually assess building characteristics. However, current predictive modelling applications - even with AI support - are generally implemented in bigger markets due to limited datasets from fewer transactions and harder-to-obtain rent information in smaller markets. Despite these challenges, opportunities exist for specialized markets through alternative data sources such as tenant location registries, construction permits, or building records, where AI can create predictive models for tenant movement patterns or building quality assessments.

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.

While smart building technologies like Hank optimize individual properties, AI's impact extends far beyond operational efficiency to transform market intelligence into strategic decision-making. JLL's Azara and Lease Navigator AI platforms exemplify next-generation market intelligence.

Azara’s system breaks through traditional dashboard limitations by allowing users to ask questions in natural language, which converts into SQL queries (commands written in the Structured Query Language used to retrieve, update, insert, or delete data from a database) and returns results instantly. Users can ask complex questions and receive immediate answers, followed by comparative analysis against previous quarters or predictive forecasting for future periods. The platform is aggregating data from workplace services, building operations, IoT sensors, and various building assets into a centralized, normalized data foundation.

Lease Navigator, a multi-agent AI solution designed to help companies manage their entire portfolio of real estate leases, is acting as the central nervous system for their leased properties. It works with a team of specialized "agents”, which can be thought of as individual automated programs - each performing a distinct task, much like a team of human specialists. These retrieval, analyst, portfolio advisor, and action coordinator agents, work in concert to analyze both unstructured documents and structured databases. Their primary functions are to provide comprehensive support for lease administration, lease accounting and compliance, data analytics and reporting, and portfolio optimization.

These platforms demonstrate that AI's true power in CRE lies not just in optimizing individual assets, but in transforming vast, complex data into a strategic advantage. By turning market intelligence into actionable insights, these tools are fundamentally changing how portfolio-level decisions are made. This technological leap from data to strategy brings us to the most critical component in the equation: professionals whose expertise is amplified by it.

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.

In the evolving landscape of CRE, the most profound transformation is not driven by Artificial Intelligence alone, but by its thoughtful integration with human expertise. This is the core of a human-centric approach: building a future where technology serves as a powerful amplifier for professional intellect, not a replacement for it. The question is no longer whether AI will reshape our industry, but how can we use its power to augment our capabilities and create lasting, human-driven value. The urgency of this mission is clear: recent JLL research found that by mid-2025, an astonishing 92% of companies had already initiated AI pilots, and their focus is sharply defined. The number one use case is real estate data-related workflows, with portfolio optimization and sustainability also ranking as top priorities.

This human-centric evolution is fueled by a "data generation revolution” with the ability to create structured, usable data. This capability is the raw material that, in the hands of an expert, builds tangible results, affirming a core philosophy: the true power of AI is unlocked only when embedded within expert-led services. This ensures that data-driven insights are translated into actionable, context-aware strategies that navigate local regulations, physical asset constraints, and unique financial opportunities. Based on latest JLL research findings, the top budget priority for occupiers over the next five years is strategic advice on technology and AI, showing they are actively seeking partners who can translate data's potential into real-world value.

The future of real estate is not being coded by AI; it is being designed by people, for people, with the support of AI. The result is a CRE industry that is more predictive, sustainable, and strategically agile than ever before. This future will be built on the partnership between augmented intelligence and irreplaceable human insight. By thoughtfully pioneering this integration, we are not just participating in the industry’s evolution, we are actively shaping its future, ensuring our clients are equipped not only to navigate the changes ahead but also to lead them.