The future of AI in CRE

JLL’s latest Global Future of Work survey 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.

This means a new hybrid work model (Hybrid 2.0) is imminent, blending manual and automated processes, with AI supporting human experts across business functions. In this emerging work style, CRE is no exception. 

The weight of expectation on new technology inevitably leads to disillusionment when people run into difficulties implementing it successfully. This is not necessarily due to problems with the technology itself but because of unrealistic expectations and practical issues which appear as companies begin their AI pilots. Such failings may be due to incoherent strategies, impractical use cases, insufficient digital infrastructure or poorly organized data.

The FOW survey reveals that CRE is now close to this disillusionment phase. Survey responses show a gap between C-suite enthusiasm and on-the-ground implementation. For example, almost 70% of business leaders say they have an AI strategy in place for their CRE function and are piloting use cases. However, only 33% of senior managers report that they have an AI strategy in place. This strategy and implementation gap also exists between global and local functions.

Myths abound around AI and its implementations, such as “AI will take my job,” “AI can automatically tell me what to do” or “AI is not yet mature enough for any meaningful CRE use.” While containing kernels of truth, these myths portray AI as an abstract concept with mysterious theoretical capabilities. 

In reality, however, AI serves as a product feature with clear boundaries of what it can or cannot do. Companies need to ground their understanding of AI in the context of viable product offerings which deliver measurable values for CRE. This understanding will naturally debunk myths that have hindered AI adoption and recalibrate companies’ expectations in formulating actionable AI strategy.

For CRE, there are two primary categories of AI tools being used today:

CRE professionals need to consider where their top priorities are, existing work patterns, systems already in place, availability and capabilities of products in the market and of course the cost of implementation and current budget. This process, focused on usefulness, will identify the most meaningful AI use cases from tangible possibilities and prioritize them according to the company’s specific conditions:
 

• Location strategy: market positioning, trend analysis, cost analysis, optimized financing, streamlined site selection
• Portfolio optimization: data standardization and reporting, risk assessment, space forecasting, scenario planning, stress-testing portfolio strategies
• Design, fit-out and construction: fast design iteration, supply chain optimization, cost estimation, dynamic schedule optimization, construction site monitoring
• Lease administration: standardized lease abstraction, automated document management, compliance monitoring, automated auditing
• Sustainability strategy: energy analytics and modeling, dynamic energy sourcing, scenario-based decarbonization roadmap, automated HVAC systems
• Workplace and occupancy: Floorplan digitization, occupancy sensing, space utilization pattern detection, dynamic occupancy planning 
• Operations and maintenance: Predictive maintenance and cleaning, inventory analysis and procurement optimization, automated recordkeeping
• Employee experience: personalized environment control, intuitive room and desk booking with automated calendar updates