Artificial intelligence is increasingly being used in corporate real estate to automate routine tasks, analyse large datasets and help companies make decisions on property portfolios, workplace strategy and locations.
A recent example from Colliers shows how AI can help businesses maintain operations during disruptions. When an energy company was hit by a cyber attack that disabled its systems, it was unable to process rent payments or access email. The client provided more than 40 screenshots of landlord information from a mobile phone.
Colliers’ Lease Administration team used AI-powered optical character recognition (OCR) to extract information from the images. The system achieved about a 90% data capture rate, allowing the team to notify more than 400 landlords about delays in rent payments within the required timeframe.
AI is also being applied to portfolio strategy. Colliers says its machine-learning tools can analyse information such as office locations, property sizes, lease expiry dates and employee numbers to identify potential savings. The company estimates that this can increase the speed of portfolio analysis by about 80%.
In workplace advisory, machine learning can analyse employee surveys, occupancy data and other workplace information to identify patterns and improve the use of office space. Generative AI can also support the creation of floor plans and 3D workplace designs.
Location intelligence is another area where AI is gaining importance. By analysing workforce demographics, market conditions, talent availability and other factors, predictive tools can help companies identify locations that better match their hiring and business requirements.
Colliers cites an example in which data analysis showed that a company’s key hiring markets had relatively low diversity among targeted talent groups. The company subsequently opened an office in a market with a stronger and more cost-effective talent pool.
The next stage could involve AI systems making more proactive recommendations, including identifying portfolio risks, suggesting locations, managing critical lease dates and supporting project planning.
However, the increasing use of AI also places greater importance on data quality, human oversight and responsible decision-making, particularly where property, financial and workforce decisions are involved.
