Just 5% of CRE companies have achieved their AI goals. Here’s why
News Summary
The commercial real estate (CRE) market is accelerating its adoption of artificial intelligence (AI), moving beyond initial testing to more targeted applications aimed at redefining value. A new JLL survey indicates that while still in early stages, organizations are prioritizing AI in their technology budgets and shifting focus from mere efficiency to business growth. According to the survey, 88% of investors, owners, and landlords have started piloting AI, pursuing an average of five use cases simultaneously, and over 90% of occupiers are running corporate real estate AI pilots. This marks a rapid increase from just 5% two years ago. However, only 5% of respondents reported achieving all their program goals, with nearly half achieving two to three. The primary reason for not fully meeting goals is that companies are now tying AI to revenue objectives rather than just operational efficiencies. For instance, some are using AI to enhance investment risk models, demanding significant changes to fundamental operating methods. Despite economic headwinds, substantial investments are being made in AI, with over half of surveyed investors seeing significant budget growth, primarily for strategic AI advisory, cybersecurity and data security upgrades, and AI integration infrastructure. Surprisingly, companies are focusing AI on competitive advantage and pressing business problems, rather than simple, low-risk operations.
Background
The commercial real estate (CRE) sector has historically been slow to modernize technologically, making the current acceleration in AI adoption particularly noteworthy. Over the past few years, the global economy has faced multiple challenges, including high inflation, rising interest rates, and geopolitical tensions, prompting businesses to seek new growth engines and cost-saving solutions. JLL, a leading global real estate services and investment management firm, provides an authoritative perspective on the state of AI adoption through its survey. In the current 2025 market environment, the economic policies of the Donald J. Trump administration, particularly its potential impact on interest rates and the real estate market, may further incentivize CRE firms to leverage technological innovation for competitive advantage and risk management.
In-Depth AI Insights
What are the underlying drivers for the accelerated AI adoption in CRE, despite historical tech skepticism and current economic headwinds? - Defensive Innovation & Competitive Pressure: The CRE market faces challenges from widespread remote work, high interest rates, and asset valuation pressures. The accelerated AI adoption could be a defensive strategy to navigate these headwinds by optimizing operations, enhancing asset value, and improving decision-making, avoiding being outpaced by more technologically advanced competitors. - Data Richness and Value Extraction: CRE is a data-intensive industry, with vast untapped data from tenant behavior, energy consumption, and market trends. AI offers the potential to extract insights, identify patterns, and drive revenue growth from this data, going far beyond simple efficiency gains. - “Innovate or Perish” Mentality: Despite traditional caution, the success stories of AI adoption in other industries have prompted CRE leaders to recognize that ignoring AI will lead to long-term competitive disadvantage in the digital age. The current rapid adoption reflects an “innovate or perish” urgency, especially amidst increased market uncertainty. What are the broader investment implications of CRE firms shifting their AI focus from efficiency to revenue generation, especially given the low success rate so far? - Increased Strategic Capital Expenditure: This shift implies that companies view AI as a core business strategy rather than a peripheral IT expense, likely leading to significant capital expenditure increases in AI-related technologies, talent, and infrastructure over the coming years. Investors should monitor companies with clear AI revenue models and strong execution capabilities. - Demand for Specialized AI Solutions: As CRE firms seek revenue growth, the demand for specialized AI solutions capable of providing advanced analytics, predictive modeling, and automated investment decision support will surge. This bodes well for PropTech companies with deep industry understanding and AI expertise. - Market Consolidation and Winner-Takes-All Dynamics: The fact that only a fraction of companies are achieving their AI goals suggests potential market consolidation. Companies effectively implementing AI and translating it into revenue growth will gain significant competitive advantages, possibly leading to a “winner-takes-all” scenario within the industry and challenging laggards. How might the Trump administration's economic policies, particularly regarding interest rates and real estate, influence the risk/reward profile of these AI investments in CRE? - Interest Rate Policy's Impact on Capital Costs: The Trump administration's policies could lead to interest rate volatility or sustained high rates, directly impacting financing costs and expected returns for CRE projects. A high-interest rate environment increases the cost of capital for AI investments and demands higher ROIs to justify them, raising the risk threshold for undertaking AI projects. - Regulatory Environment and Data Security: While the article mentions investment in cyber and data security, the Trump administration's stance on data privacy and AI regulation could influence the deployment of AI tools and data utilization. Investors need to assess whether potential regulatory shifts might increase compliance costs for AI solutions or restrict their scope of application. - Infrastructure and Investment Incentives: Should the Trump administration pursue large-scale infrastructure initiatives or offer new investment incentives, it could stimulate demand in specific CRE segments (e.g., industrial, logistics), indirectly supporting AI investments within those areas. However, any protectionist trade policies could also affect global supply chains, impacting AI demand for warehousing and logistics properties.