GENERATIVE AI is set to drive significant opportunities for the Asia—Pacific corporate real estate (CRE) sector in the years ahead, according to a new report from global diversified professional services and investment management company, Colliers.
The report, “AI in corporate real estate: The now, the next and the possible,” found the flourishing generative AI market in APAC has untapped potential for achieving new levels of productivity, creativity, and efficiency in the CRE sector.
“For CRE, AI is going to impact every service line by creating new tools to improve service delivery,” Mike Davis, Colliers managing director of Occupier Services, Asia Pacific, said.
“Whether it’s looking for a new location, understanding how to optimize a portfolio or designing the right space for a client’s employees, AI will allow us, in the CRE industry, to use more data, faster, and provide more options to make informed decisions.”
According to Dom Fredrick Andaya, Colliers executive director and head of Office Services — Tenant Representation: “The CRE industry thrives on swift and accurate decision-making to accommodate the fast-paced and emerging APAC markets. AI can assist negotiators in processing huge volumes of real estate data, analyzing market trends and opportunities, generating forecasts through existing economic indicators, and anticipating future real estate market challenges. Incorporating AI in the workplace can improve operational efficiency as negotiators take control of it as a tool to meet their client demand across the region.”
According to the report, AI can potential impact service delivery in the following key areas of CRE:
– Workplace Advisory: Machine learning can collect and analyze data from surveys, feedback systems, and social platforms to assess company culture and other desired areas of interest. Generative AI can also be used to generate floor plans, create realistic 3D renderings, and conduct test fittings.
– Lease Administration: Natural Language Processing used through Optical Character Recognition technology streamlines the lease abstraction process and improves data accuracy, while machine learning enhances critical date management by automatically tracking and reminding lease administrators of important deadlines.
– Portfolio Strategy: Predictive analytics is potentially crucial in continuously optimizing portfolios. Machine learning can provide analysis of key measures, align to core KPI’s and provide recommendations on market, location, and timing recommendations as well as recommend new developments and optimal mix of properties in a portfolio.
– Facility Management: Predictive analytics can also be used to help implement proactive maintenance for energy cost reduction, enhance cost prediction, asset lifespan assessment, depreciation quantification, and insights into future maintenance and improvements. Machine learning will help act as a concierge, serving as the first line of communication for tenants. Predictive analytics will be able to assess future occupancy requirements and help determine commensurate onsite service levels.
– Project Management: AI can help in making recommendations to lower maintenance cost and optimize resource allocation. This will enable project managers to make well-informed choices that reduce wastage, result in cost savings, and ultimately lead to the best project outcomes.
