Commercial Real Estate Braces for AI-Driven Footprint Compression Across Asia-Pacific

Artificial intelligence is beginning to reshape demand for commercial office space across Asia-Pacific, as companies automate routine tasks and compress physical footprints in back-office and support functions, according to new analysis from Cushman & Wakefield's CLI division tracking occupier behavior in the region.

The property consultancy's research indicates that while AI is eliminating certain tasks, it is simultaneously creating new categories of work—a pattern consistent with historical technological shifts. Roughly 60 percent of US workers today hold jobs that did not exist in 1940, and technology has driven 85 percent of employment growth since then, the firm noted. AI-driven efficiency gains are now tightening headcount-to-desk ratios, prompting some occupiers to actively consolidate their real estate holdings.

Industries most exposed to AI adoption saw three times higher growth in revenue per employee compared to those least exposed, suggesting the technology's impact extends beyond cost reduction to revenue and productivity enhancement. The shift is compressing space needs particularly in administrative and support functions, where automation is most readily applied.

Meanwhile, a new metric for assessing national competitiveness in the AI era is gaining traction among investors. Morgan Stanley analysts recently proposed measuring "Gross Domestic Intelligence," or GDI, which quantifies access to AI compute infrastructure including GPUs, networking gear, and data centers. Epoch AI estimates from the fourth quarter of 2025 show the United States commanding roughly 75 percent of global AI computational power, with China holding about 10 percent. Among individual companies, Google dominates with proprietary TPUs and substantial Nvidia GPU holdings, and every top-ranked firm by compute capacity is American. China's total AI compute capacity is comparable to that of Oracle alone, according to the research group backed by Dustin Moskovitz's Coefficient Giving charity.

Yet the deployment of AI tools is outpacing workforce readiness, creating bottlenecks to productivity and return on investment. "Employers aren't giving their people the skills, understanding, or ethical grounding they need to succeed with AI and it's becoming a clear bottleneck to productivity and ROI," said JP Gownder, vice-president and principal analyst at Forrester. The firm's research shows most organizations are rolling out AI tools without investing in employees' ability to use them effectively, requiring a shift toward continuous, hands-on learning that demystifies the technology and addresses employee concerns.

In India, corporate workforce planning reflects this tension. Pay remains the primary driver of attrition, while employees increasingly view AI skills as crucial for career advancement even as they express concerns about surveillance. Seventy-six percent of companies are planning to flatten hierarchies and 64 percent are moving toward self-organizing teams, with Indian firms showing a preference for redeploying talent rather than cutting jobs as AI reshapes roles. "What's different this year is a clear shift toward collaboration and reinvention, and organisations are now focusing on how humans and AI can work in sync, with a much stronger emphasis on continuous upskilling and building future-relevant capabilities," said Mansee Singhal, career leader at Mercer.

(Forrester's State of AI 2025 survey found that almost 70 percent of AI decision-makers are using generative AI in deployed production applications, while 81 percent of automation decision-makers say AI copilots that assist employees are important applications, indicating a growing disconnect between AI adoption and workforce preparation.)

The emergence of GDI as a potential investment overlay reflects a broader recognition that AI compute capacity may become as strategically significant as traditional measures of industrial output. Epoch AI, a research group that tracks AI development and impact, has positioned computational power as a proxy for national competitiveness, with implications for capital allocation and geopolitical positioning. The concentration of AI infrastructure in American firms—particularly Google, Microsoft, Amazon, and Meta—underscores the technology's role in consolidating economic power among a narrow set of actors, even as its effects ripple across sectors and geographies.