The commercial real estate industry is entering a new phase of technology-led transformation. Rising energy costs, resource constraints, changing regulations, and evolving tenant expectations are pushing building owners to rethink how they manage their properties. In this shift, AI in commercial real estate buildings is becoming a practical tool for improving performance, efficiency, and occupant experience.
Artificial intelligence can help building teams analyze data from HVAC, lighting, energy systems, occupancy sensors, and maintenance platforms. These insights make it easier to identify inefficiencies, predict equipment issues, optimize comfort, and support smarter decision-making. As buildings become more connected, AI can help commercial real estate leaders unlock greater operational value.
In our recent webinar, “AI in Buildings: Enhancing Performance and Value,” we discussed with industry leaders from Arup and PIMCO Prime Real Estate AI’s transformative potential in the commercial real estate sector. Early technology adopters using AI are revolutionizing their building design, operational performance, and asset management, delivering sustainability and financial gains.
The urgent need for transformation
Commercial buildings significantly contribute to global greenhouse gas (GHG) emissions, accounting for approximately 40% of all greenhouse emissions. With 80% of today’s existing buildings expected to still be in use in 2050—the same target year for meaningful carbon footprint reduction—decarbonizing the building environment is an urgent priority.
Alongside environmental concerns, the industry faces evolving tenant expectations. While commercial buildings may offer occupants desirable on-site amenities and fast internet connections, AI takes it one step further to create “smart offices” that proactively respond to occupant and business needs. These smart, digital workspaces help facility managers right-size spaces and monitor real-time usage patterns. AI also enhances transparency, providing tenants with real-time data on building performance.
Meanwhile, landlords are under pressure to optimize building operations, gain deeper market insights, and demonstrate compliance with tightening environmental regulations. These laws span various areas, from water management (e.g., PFAS and stormwater control) to waste disposal, land use planning, and conservation. Adapting to these demands is essential for maintaining competitive and sustainable properties.
AI: A catalyst for change
The convergence of these factors lays fertile ground for AI adoption in the building industry. Recent technological advancements, including the exponential growth of data availability and the capacity to train sophisticated AI models, make AI-powered solutions more accessible and impactful than ever.
Rising energy costs and climate variability further propel AI to the forefront of innovation. The commercial real estate industry is relatively optimistic for 2025. A recent Deloitte survey found that 81% of global respondents identify data and generative AI intelligence as areas to focus spending for the coming year. Increased budgets are expected to accompany this renewed optimism.
However, consistent data is one of the biggest barriers to transforming our buildings. High-quality AI outcomes require high-quality data, and the industry is progressing in extracting better data. However, 90% of the data we use today was created in the last two years, and we must improve our ability to aggregate and structure data better.
So, why haven’t more building owners adopted AI yet? While real estate typically adopts new technologies more slowly, we must immediately start. According to a recent McKinsey study, AI could generate up to $180 billion in new value for the real estate industry. That means we need to accelerate AI adoption across our sector.
Early success for AI in buildings applications
We’ve observed early success in commercial real estate buildings leveraging AI, dependent on the building’s lifecycle:
- Design and construct more sustainable buildings: AI-driven tools allow engineers to consider sustainability metrics from the earliest design stages, including elements like low-carbon materials, optimizing shade, and maximizing solar utilization. These intelligent AI-driven designs can contribute to more aesthetically pleasing and environmentally responsible buildings.
- Operate and maintain to reduce a building’s environmental impact: HVAC systems are often the primary energy consumers in buildings. AI uses real-time data on occupancy, weather patterns, and a building’s thermal properties to optimize HVAC settings, achieving an optimal balance between energy efficiency and occupant comfort. AI-powered predictive maintenance can help minimize the risks of costly repairs.
- Full asset lifecycle to enhance the tenant experience: AI transforms facility management by providing actionable insights from analyzing data points across the building. Now, facility managers can make proactive, data-driven decisions that strengthen asset and operations performance. AI is being leveraged to optimize HVAC systems, manage microgrids, and predict maintenance needs, helping enhance the full tenant experience.
As building operations become more connected, AI will play a larger role in how commercial real estate creates, measures, and sustains value. The future of AI in smart buildings 2025–2030 will depend on strong collaboration, trusted data, and the right AI-powered solutions working together across building systems.
For owners, operators, and facility teams, this means moving beyond reactive maintenance and manual reporting. AI can help improve performance, optimize energy use, enhance occupant comfort, and support smarter investment decisions.
Building a data-driven culture today will make it easier to unlock long-term value as smart building technologies continue to evolve. Discover how AI is transforming building operations in our latest webinar, “AI in Buildings: Enhancing Performance and Value.”
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