• Corporate real estate (CRE) AI adoption transforms the industry: The percentage of corporates piloting CRE AI solutions in APAC has surged dramatically from < 5% to 92% over three years, and AI-initiatives are now top priority in real estate tech budgets.

• Business priorities drive AI pilot focus: With 65% of APAC corporates facing CRE tech budget constraints, CRE teams are strategically channeling resources to priority use cases like portfolio optimization, energy management, and data-related workflows that support C-suite business objectives.

• A systematic AI roadmap strategy supported by a skilled workforce is the cornerstone of success: Corporates with successful CRE tech programs are characterized by a more systematic and innovation-driven approach to their AI roadmap and talent development strategy respectively.

Artificial intelligence is driving a profound transformation in Asia Pacific's commercial real estate (CRE) industry. Our latest findings from the JLL Global Technology Survey 2025, which gathered insights from over 1,000 senior decision-makers globally, including 380 occupiers across key APAC markets and industries like financial services, technology, and life sciences, have found that AI has rapidly evolved from a futuristic concept into a central business imperative, transforming the entire real estate lifecycle.

The pace of CRE-AI adoption in Asia Pacific has been staggering, with pilot programs soaring from under 5% to 92% in just three years. This surge represents a collective recognition that standing still is no longer an option. The advantages offered by AI—from energy tracking analytics to anomaly detection—are too significant to ignore, and companies are racing to capture the benefits for a competitive edge. 

Despite limited budget growth in the past 2 years, this urgency is clearly reflected in corporate spending, with real estate technology budgets being reallocated to fund this transition. The survey findings reveal that the top budget priorities for CRE teams are in preparation for AI implementation or its impact through upgraded cybersecurity and digital infrastructure. Corporates are recognizing the need for expert guidance to achieve value on its costly AI investments, and this is evidenced by 64% of APAC corporates prioritizing spend on strategic advisory for technology and AI, the top budget item.

With 65% of APAC corporates reporting pressure in securing budgets for CRE technologies, every dollar must be strategically deployed. A broad range of AI pilot trials across CRE processes are underway, with 76% of APAC corporates pursuing 2-4 pilot areas out of the 10 broad use cases surveyed. Corporates are going beyond simple and low-risk applications of AI, such as lease administration which is considered well-suited for Generative AI due to its document-heavy and silo-ed nature. Resource constraints have led corporates to favor AI pilots that best align with business strategic goals and which they expect will solve their most pressing business challenges.

The critical objectives prioritized by the C-suite for the next 3 years rank reducing operating costs through portfolio optimization at the top (94% rating as important), followed by boosting workforce productivity (93%) and achieving organizational efficiency (92%). This aligns with the top three areas for AI pilots in APAC which are real estate data-related workflows (prioritized by 53% of corporates), portfolio optimization (48%), and energy management (42%).

1. Real estate data-related workflows 

CRE teams manage a wide spectrum of complex datasets covering energy consumption, payment and procurement, workplace experience, and more. Real estate data has historically been fragmented, with information often in siloed systems and stored with inconsistent formatting and terminology, undermining the effectiveness of insights generated to support decision-making. Organizations are now deploying AI to address this core challenge by standardizing formats, integrating disparate data sources, and digitizing static documents. While these measures may not generate direct cost savings, they are critical for building the foundational data infrastructure necessary for subsequent AI applications.

2. Portfolio optimization

In response to economic uncertainty, agile portfolio optimization has become a top priority for business leaders seeking to reduce operational costs. The shift to continuous space planning for rightsizing the portfolio and cost management requires processing immense datasets—a task well-suited for AI. Consequently, CRE leaders are actively piloting AI to drive significant efficiencies in portfolio analysis, optimization strategy, and capital planning. In fact, the top AI pilot use case among APAC corporates is leveraging AI as a tool to generate data-driven predictive insights for portfolio optimization strategy.

3. Energy management

Driven by sustainability goals and cost-reduction pressures, 93% of APAC respondents agree that sustainability, energy efficiency and decarbonization remain key drivers for technology adoption, and energy management has become a prime target for AI. Initiatives focus on energy tracking, decarbonization planning, and automated HVAC controls to enhance efficiency and meet compliance mandates. Energy management is considered a mature AI category that offers immediate and measurable returns on investment, making it a compelling use case. 

Barriers to AI adoption

Despite the many benefits to AI implementation, some corporates have still not embarked on any AI pilot for their CRE function. Of this group, a significant 61% point to the lack of a clearly defined AI strategy as the main barrier, while 52% cite concerns over cyber and data security. This hesitation is compounded by a distinct risk-averse culture in the APAC region, with 35% preferring to wait for others to test first—almost double the global average. This combination of strategic uncertainty, security fears, and a preference for proven solutions has created significant inertia for these corporates.

On average the maturity of AI in CRE is still low, and while the implementation intent is there, many corporates are struggling to realize the benefits they expect. For instance, while improving CRE team productivity is a top goal, only about half of corporates in APAC feel they have achieved this to a large extent. The gap is even wider for more complex goals like improving business agility to meet the needs of a changing market environment, for which only one in three report success.

However, there is another "tech maturity gap" that is emerging, which shows that the ‘leaders’ which have been running a successful tech program have clearly surpassed the rest in the extent they have achieved their CRE AI benefits.

AI technologies on their own are clearly not what separates the leaders, who are successfully translating AI investment into tangible value, from the rest of the pack. Looking at their characteristics and processes may shed some light on the most important differentiators. 

1. Foundational planning is a key differentiator

Corporates with successful CRE technology programs are distinguished by their thorough planning. They are more than twice as likely to audit their existing technology, processes, and data portfolio-wide and to establish clear KPIs to measure success in their technology investments. They also establish cross-functional teams uniting CRE, HR, Finance, and IT to clarify responsibilities, driving accountability and ensuring enterprise-wide alignment.

Upgrading legacy and ineffective systems is also of key importance, as legacy systems are a major barrier to AI adoption, creating both security vulnerabilities and operational drag. 74% of APAC corporates are planning to retire or upgrade at least one technology system, and 87% are planning to allocate budget for upgrading within this year or next year. These corporates recognize that a robust digital infrastructure is an essential foundation to support AI adoption while protecting data and safeguarding business continuity.

2. Invest in upskilling workforce for AI

This organized approach extends to upskilling their workforce. Successful corporates are more likely to take a proactive innovation-focused approach to upskilling, implementing formal training programs that encourage employees to explore, test and innovate with AI within a sandbox environment. This proactive approach can be critical to closing a major skills gap: JLL’s Workforce Preference Barometer 2025 research found that only a third of office employees in APAC feel adequately trained to use AI in their job, and older employees in particular report the lowest confidence levels. 

3. Time AI rollouts for maximum buy-in

To maximize buy-in and resource allocation, embed AI initiatives within existing corporate decision-making cycles. One in two decision-makers in APAC consider the capital planning cycle and organizational restructuring as the most opportune moments to introduce new technology. Aligning with these events creates opportunities to secure resources and engage a workforce that is already navigating change.

The question facing leaders is no longer if they should adopt AI, but how to generate tangible returns. As this research shows, successful firms distinguish themselves through rigorous preparation, not just bigger budgets.

What organizations can do to get value from their AI investments:

• Plan for value, not just technology: Build a roadmap founded on clear business outcomes, with KPIs to measure success at every stage.
• Build a future-proof foundation: Upgrade critical infrastructure and cybersecurity to handle the demands of AI and protect valuable data assets.
• Empower employees to innovate: Launch targeted upskilling programs to create a workforce that is confident and capable of leveraging new AI tools.

Achieving success across these areas is a complex undertaking. A strategic partner can help CRE leaders become indispensable to the C-suite, providing expertise to translate a company’s vision into a value-driven execution plan, and ultimately turning ambitious goals into concrete results.