As the capabilities of AI agents continue to astonish the world in 2025, AI is becoming increasingly powerful.
 

• AI has enormous potential to reshape real estate, with near and long-term impacts ranging from the emergence of new markets and asset types to innovations in investment and revenue models.
• A rapidly expanding AI ecosystem and its supporting infrastructure will drive demand for real estate in different markets across the globe.
• There are increasing number of AI-powered real estate technology solutions. Organizations will need to consider how they can harness AI strategically and ethically, piloting applications before scaling to deliver value.

The potential for artificial intelligence (AI) to transform businesses, industries and society has been mounting for decades. But recent advancements, have moved the science from niche to mainstream. The technology’s proficiency in writing, drawing, coding and composing has compelled corporate leaders to consider both the opportunities and threats that AI presents for their future.

For commercial real estate, it’s clear that strategically embracing AI could transform the sector. JLL’s latest Global Future of Work survey published in Jan 2025 confirms that AI is already being actively implemented in the business world. More than nine in ten C-suite leaders believe AI will change the way the workforce operates over the next five years. A similar proportion plans to accelerate investment in AI over that period. 

Yet, the survey also shows a lack of thorough understanding of the technology, it’s impact and a systematic approach to its implementation.

AI uses machine learning and deep learning algorithms to perform tasks that require the ability to learn from experience, understand complex concepts, recognize patterns, interpret the nuances of natural language and independently make decisions. Generative AI is a subset of AI that focuses on creating new content, designs or solutions.

AI’s impact in the real estate market

AI sector as real estate occupiers

The real estate industry as AI adopter

With AI, we anticipate a similar five-fold impact in the long run. While it remains to be seen how AI will be applied to specific sectors like healthcare and how much this growth will generate space demand, some influences are already emerging.

1. Geolocation: AI companies and investments have been observed to cluster around established tech markets. Going forward, growth is likely to be concentrated in locations where AI talent is available, namely tech hubs, innovation centers and universities.

2. Altered demand among assets: AI development calls for more and better data centers, energy grids and connectivity infrastructure.

3. New asset and product types: the birth of the ‘real intelligent building’ is imminent. AI-compliant infrastructure will become a default just as internet connections are a default feature of current buildings. AI will also help deliver net-zero buildings with high sustainability performance.

4. Revenue and investment: AI-powered underwriting and processes will enable faster transactions and more efficient understanding of properties and markets, catalyzing investments at a global scale. AI-compliant infrastructure and the ability to plug in multiple systems could also enable the expansion of ‘space as a service’ models and new revenue streams for landlords and developers.

5. Design and space function: AI will allow for experience-driven design and highly customizable environmental settings.

Read more about this topic in JLL’s Future Vision series - Get set for the 5th Industrial Revolution Real estate strategies for an AI-powered world

AI sector as real estate occupiers
 

The growing AI ecosystem will continue to expand in selected tech hubs

Foundation model developers, such as OpenAI, are just the tip of the iceberg when it comes to the AI ecosystem. Companies involved in semiconductor hardware, cloud computing platforms, model hubs and application development all represent a growing occupier segment. The commercial real estate opportunity looks even brighter when considering the additional companies that will emerge as pre-trained foundation models are modified for specific use cases.

In 2024, private investment in AI within the US alone hit US$109 billion, doubling the amount in 2023. China showed the second largest investment of US $9.3 billion. The AI focus area with the most investment was medical and healthcare; followed by data management, processing and cloud computing; and Fintech. Additionally, enterprise use cases for generative AI represent a substantial opportunity. The GDP related to AI is anticipated to grow with a 18.6% compound annual growth rate (CAGR) through 2030 (PwC). According to our research, the growth in AI is also translating into increased real estate demand from this sector. In the US alone, AI companies nearly doubled their footprint in just two years, occupying more than 2.04 million square meters. This footprint is expected to grow  to 5.2 million square meters in 2030.
 

37% of AI companies are based in the U.S.

JLL research shows there is an accelerating demand for AI talent, with AI job postings increasing by over 250% since the beginning of 2021. In the longer term, this means growth is likely to be where AI talent is available, namely primary and established secondary tech hubs, innovation centers and universities.Due to specialized skills required to build language models, AI CRE growth may remain in gateway cities for the next several years.

Training and using AI requires considerable resources and supporting infrastructure
 

Generative AI is built upon vast computing power and extensive resources. Training and inferencing AI requires infrastructure such as computing hardware, high-speed connectivity networks, power supply, cloud infrastructure and data storage that all must be housed somewhere. Additionally, the continuous expansion of AI applications will drive the need for more power, more cooling facilities and more data centers. Manufacturers and vendors of GPU and network switches will also grow, and thus require space as occupiers.

Colocation, hyperscale and edge data center markets will continue to expand globally
 

This technological revolution of AI is not merely evolving the digital infrastructure landscape; it's fundamentally redefining it. According to the 2025 JLL Global Data Center Outlook, the exponential progress of artificial intelligence (AI) and machine learning is fueling a wave of transformative shifts in data center design, site selection, and investment strategies. To keep up with the growing demand for computational power, hyperscale data centers are projected to increase their rack density at a compound annual growth rate (CAGR) of 7.8%.

AI infrastructure location criteria gives more weight to lower energy prices and lower land costs. Factors such as competitive energy pricing and energy consumption regulations are driving growth toward less crowded markets such as Atlanta in the U.S., Malaysia and Thailand. While edge data centers continue to grow near major cities to be close to the users, a more dispersed distribution is being observed in the infrastructure underpinning AI.

AI also drives new data center design requirements. Data centers in the AI era need to accommodate evolving hardware needs, such as advanced liquid cooling facilities.

Read more about this topic in JLL 2025 Global Data Center Outlook

The real estate industry as AI adopter
 

The PropTech sector has laid a solid foundation for AI integration into real estate applications

The real estate industry has begun to proactively embrace and adopt new technologies.. In JLL‘s 2024 Future of Work Survey, most companies (90.1%) expect to carry out corporate real estate activities, such as workplace strategy, occupancy management and lease administration, with AI supporting human experts over the next five years. Over 60% have already started piloting different AI use cases in their real estate functions.

This is powered by a maturing PropTech ecosystem. There are now technological solutions for almost every aspect of real estate functions, including investment management, design and construction, building and facility operations and portfolio management. A solid foundation has been laid for AI integration.

Globally, there are over 500 companies providing AI-powered services to real estate and already delivering value in terms of improved efficiency and cost-savings. Top use cases of AI include:

• Document sorting and data standardization for portfolio data analytics and benchmarking
• IoT data mining for automated facility management
• Price modeling and prediction for investment management
• Satellite image processing for asset valuation and risk management
• Reality capture for construction site monitoring
• Scheduling for construction and capital project
• Recommendation and matchmaking for leasing and investment transactions
   

Generative AI applications in real estate are still in the early stages
 

Emerging use cases cover client communication assistance in leasing and property management (such as chatbots to handle tenant queries), floorplan and design generation and summarizing unstructured documents to create reports. More products are expected to come onto the market soon. Large Language Models, in particular, provide the ability to extract insights from vast amounts of text-based documents in real estate, significantly reducing the complexity of multi-lingual, multi-national operations.

However, most companies still lack a systematic approach to their AI implementation. The ability to develop actionable strategy is going to be the key determining factor for successful integration.

Read more about AI adoption in The future of AI in CRE - Why corporate real estate needs a systematic approach to AI

Early adopters of AI-enabled solutions are already seeing returns
 

Royal London Asset Management, a leading UK investment firm, experienced significant improvements in HVAC operations and energy efficiency in an 11,600 square meters commercial office building. By implementing JLL’s AI-powered Hank technologies, the firm has reached a record ROI of 708% and energy savings of 59%, reducing carbon emissions by up to 500 metric tons per year.
 

Case studies: AI creating value for real estate