AI drives predictive strategy and design in real estate
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AI drives predictive strategy and design in real estate

AI is urging firms to adopt data fluency and new tools.

Artificial intelligence is reshaping corporate real estate, with 73% of Colliers and CoreNet Global survey respondents expecting a significant impact. Over 60% have adopted or plan to adopt AI strategies within 18 months, signaling a shift to data-driven decision-making.

Mike Davis, Managing Director of Occupier Services, Asia Pacific at Colliers, said AI is helping real estate teams speed up strategic planning and move from reactive to predictive modes of operation.

“Using machine learning to mine large pools of portfolio data will allow real estate teams to develop portfolio strategies in a fraction of the time,” said Davis. “AI models will soon be able to forecast market trends, tenant demand and economic shifts, helping corporate real estate leaders proactively adjust their portfolio strategy.”

AI is also playing a growing role in location intelligence. “It can enhance that location intelligence by enabling real-time monitoring of footfall and traffic and also forecasting future trends of things like urban growth and economic shifts,” Davis added. “It can assist in evaluating proximity to transportation hubs and amenities, and then modeling how accessibility impacts foot traffic, employee commute times and customer convenience.”

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James Wong, Chairman of Hon Kwok Land Investment Co., Ltd and Chair of ULI Asia Pacific Technology and Innovation Product Council, said many in the industry are still figuring out the limits of AI. “We’ve broken AI into three levels,” Wong explained. “The sort of stuff that Mike is talking about, forecasting, customer service, scheduling, personnel even, is what we call level one. Everybody’s got to do that. But that just is what in the finance world you call beta. You’re just following the market to create alpha.”

In terms of operational management, Davis noted that AI can help automate lease abstraction and reduce maintenance costs by predicting equipment failures. “It can provide real-time insights into how the space is actually being used,” he said. “You can analyse occupancy data, badge swipes and IoT sensors to identify underutilised areas, enabling smarter space planning and cost savings.”

To keep up, professionals must evolve. “Real estate professionals now have to really up their AI game,” Wong said, citing AI-powered interior design tools that leasing teams are beginning to use. “This kind of interaction… used to be outsourced to somebody else.”

Davis emphasised the importance of data literacy and digital fluency. “Skills in data visualisation, basic statistics and the ability to ask the right questions of AI will be essential,” he said. “They should understand how these digital tools work and how to use them effectively.”

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