How Artificial Intelligence Is Reshaping Commercial Real Estate Operations

Artificial intelligence is changing how commercial real estate professionals work, but not in the way some predicted. Rather than replacing brokers or property managers, AI is functioning as a productivity tool that helps teams analyze data faster, identify risks more clearly, and manage projects more efficiently. Industry leaders say the technology’s most immediate impact will be reducing the time required to process large datasets, allowing professionals to focus on client relationships and strategic decision-making.

AI Speeds Up Data Analysis and Pattern Recognition

Martin Jepil, Chief Information Officer at Avison Young, explained that AI can “create connections and identify patterns that humans cannot see as quickly.” This capability is instrumental in commercial real estate, where decisions often depend on analyzing multiple data sources, from lease terms and market comparables to energy usage and tenant traffic patterns.

For example, AI can cross-reference office traffic data with energy demand to identify inefficiencies or flag unusual patterns that might indicate maintenance issues. It can also streamline lease comparisons that typically require hours of manual review. By automating these processes, AI enables brokers and analysts to focus on higher-value tasks such as client engagement, service delivery, and business development.

According to a 2024 report from Deloitte, 73% of commercial real estate executives believe AI will significantly improve operational efficiency within the next three years. The technology’s ability to process unstructured data, such as demographic trends or zoning regulations, is expanding its application across property management, investment analysis, and site selection.

Data Quality Remains a Key Challenge

While AI offers clear benefits, its effectiveness depends on the quality and consistency of the data it processes. Jepil noted that messy or inconsistent data remains a hurdle for many firms. Commercial real estate organizations are now working to integrate structured information, such as lease agreements and financial records, with unstructured sources like local planning codes, traffic studies, and demographic data.

Training AI systems to work with both traditional and non-traditional data sources is essential to improving accuracy and expanding use cases. Firms that invest in data standardization and integration will be better positioned to take advantage of predictive analytics and other advanced applications.

James Moore’s real estate advisory team helps clients assess financial systems, improve reporting accuracy, and structure data in ways that support both compliance and strategic planning.

Predictive Analytics and Investment Decision-Making

As AI systems improve, their role in guiding investment decisions is expected to grow. Predictive analytics can help firms evaluate site selection, forecast market trends, and assess development feasibility with greater precision. By analyzing historical performance data alongside current market conditions, AI tools can identify opportunities and risks that might not be immediately apparent through traditional analysis.

Commercial real estate firms using AI-driven analytics saw a 20% improvement in deal sourcing efficiency in 2024. This suggests that technology adoption is not just a productivity play but also a competitive advantage in identifying and securing opportunities.

For property managers and investors, AI can also support asset performance monitoring by tracking key metrics in real time and flagging variances that may require attention. This level of oversight helps reduce operational risk and improve cash flow management.

AI’s Role in Routine and Strategic Work

AI’s ability to automate routine tasks does not eliminate the need for human expertise. Instead, it shifts real estate professionals’ focus toward activities that require judgment, relationship-building, and strategic thinking. Brokers can spend less time compiling market reports and more time advising clients. Analysts can move beyond data entry to interpret trends and make recommendations.

This shift has implications for how firms structure their teams and allocate resources. Organizations that successfully integrate AI into their workflows are likely to see productivity gains without needing to expand headcount. However, they will need to invest in training and change management to ensure teams can use the technology effectively.

James Moore provides tax planning and consulting services to help real estate clients manage the financial and operational implications of technology adoption, including cost segregation, depreciation strategies, and compliance support.

What Florida’s Commercial Real Estate Firms Should Consider

Florida’s commercial real estate market is active, with significant development in office, industrial, and mixed-use sectors. As firms in the state evaluate AI adoption, they should consider how the technology fits into their existing workflows and whether their data infrastructure can support advanced analytics.

Key considerations include:

• Data quality and integration across systems
• Training and change management for staff
• Alignment of AI tools with business goals and client needs
• Evaluation of vendor solutions and in-house development options

Firms that approach AI as a long-term investment in efficiency and decision-making, rather than a short-term fix, are more likely to see sustainable benefits.

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