Artificial intelligence could widen the gap between Singapore’s prime and older offices, even if it reduces the amount of space some companies need.
A business with fewer employees may choose a smaller office in a better building. The prime landlord gains a tenant, while the building that tenant leaves behind faces an empty unit. Across the market, total occupied space could fall even as selected prime properties remain well leased.
This is a plausible outcome of AI adoption, but it is not inevitable. Rental affordability, relocation costs and the ability of older buildings to adapt will influence how far the divide grows.
The rental gap is already substantial
The Business Times reported on 5 October 2026 that Cushman & Wakefield estimated the Grade A rental premium over Grade B offices at 48%, up from 34% in 2019.
That widening predates any clear evidence of widespread AI-driven office downsizing. It should therefore be treated as the starting point for this discussion, rather than proof that AI has already caused the divide.
Building age and office grade also measure different things. An older property can remain competitive after refurbishment, while a newer building may have disadvantages in accessibility, layout or operating costs. The more useful comparison is between offices that meet occupiers’ requirements and those that struggle to justify their asking rents.
Why a smaller office can support a higher rent per square foot
A company’s property budget depends on both the rental rate and the area it occupies. Reducing the latter can create room to pay more for the former.
Consider this illustrative calculation, using assumed rents rather than quotations from actual buildings:
| Office choice | Area | Monthly rent per sq ft | Monthly base rent |
|---|---|---|---|
| Existing premises | 10,000 sq ft | S$8.00 | S$80,000 |
| Smaller upgraded premises | 7,000 sq ft | S$11.00 | S$77,000 |
| Upgraded premises with a smaller reduction in area | 8,000 sq ft | S$11.00 | S$88,000 |
In the second case, the company pays 37.5% more per square foot but reduces its monthly base rent by S$3,000 because it occupies 30% less space.
The third case shows the limit. A 20% reduction in area would leave the company paying S$8,000 more each month.
At these assumed rates, the company would need to reduce its area to approximately 7,273 sq ft to keep base rent unchanged. That is a reduction of about 27.3%.
These figures exclude service charges, fit-out expenditure, reinstatement, moving costs, incentives and any period of overlapping leases. Those items could outweigh the apparent rental saving, particularly over a short lease.
AI would contribute to this shift only if it changes staffing or working practices enough to make the smaller office practical. A reduction in headcount alone does not establish how much space a company can release.
The office may need a different mix of spaces
A smaller team could still require meeting rooms, quiet work areas, client facilities and space for training. Removing workstations without understanding those needs may produce an office that is smaller but less effective.
For example, a business that automates routine processing might retain teams focused on advisory work and client relationships. Its revised workplace could allocate a larger share of floor area to discussions and confidential meetings.
This is an analytical possibility, rather than an observed outcome for every business. Different activities will produce different requirements.
It also explains why usable layout matters. An efficient floor plate may accommodate a company’s needs in less leased space, while awkward columns, circulation routes, or fixed service areas can limit savings elsewhere.
Prime offices still face downside risks
Cushman & Wakefield’s AI research considers four outcomes: productivity-led expansion, gradual adoption, an AI investment bust and labour displacement. These are alternative scenarios, not a single forecast.
The distinction matters. Stronger productivity could support business expansion, whereas disappointing investment returns or substantial job displacement could weaken demand. The research also anticipates greater differentiation between adaptable offices and more standardised stock.
A building can outperform its competitors while still seeing rents fall. If the overall tenant pool contracts enough, attracting a greater share of that pool may not compensate for the reduction.
There is also a difference between securing a tenant and securing attractive income. Longer rent-free periods, fit-out contributions or other concessions can reduce the landlord’s effective return even when the headline rental rate appears resilient.
A wider premium creates an opportunity for older buildings
The more expensive prime space becomes, the stronger the incentive to examine alternatives.
A tenant whose operations do not require a prestigious address may value convenient transport, reliable building services and an affordable total occupancy cost more. An older building that delivers those essentials could remain a practical choice.
Owners should therefore assess refurbishment through the problems it solves. Improving air-conditioning reliability, lift performance, common areas, connectivity or unit flexibility may support leasing more effectively than a cosmetic upgrade alone.
However, capital expenditure needs a credible payback. The relevant calculation includes the expected change in effective rent, occupancy and operating costs, alongside the cost and disruption of the works.
For buildings with fragmented ownership, obtaining agreement for improvements to shared systems may also affect how quickly they can respond.
What would show that the divide is widening?
The clearest evidence would come from actual leasing decisions over successive renewal cycles.
Are tenants taking less space when they relocate? Are they moving into higher-grade buildings? How long do the vacated premises remain empty, and what incentives are needed to secure replacement tenants?
Those questions are more revealing than announcements about AI adoption alone. Existing leases can delay changes in occupied space, while business growth may absorb productivity gains without producing immediate downsizing.
Investors should also examine tenant concentration. Exposure to a fast-growing industry can support leasing, but dependence on a small number of occupiers creates risk if their expansion plans change.
The best buildings will need to justify their premium
AI could deepen the divide in Singapore’s office market by enabling some companies to operate from smaller, better premises. That would support selected prime buildings while increasing competition for tenants elsewhere.
But the rental premium has limits. As it rises, well-located older offices with reliable services and sensible pricing become more attractive alternatives.
For landlords, the practical task is to identify what tenants will pay for and whether the building can deliver it at a viable cost. For investors, the test is whether the purchase price leaves room for vacancy, incentives and future capital expenditure.
The most exposed properties are those whose rents depend on advantages tenants no longer value, or whose owners cannot adapt economically. AI could accelerate that pressure, making each building’s usefulness and affordability increasingly important.
Disclaimer: This article is for general information and does not constitute investment, financial or property advice. Market data and forecasts reflect sources available at the time of writing and may change. AI-related scenarios are possible outcomes, not guaranteed predictions. Rental calculations are illustrative, use assumed figures and exclude additional occupancy and relocation costs. Individual property performance will vary with location, building condition, tenancy terms and market conditions. Readers should independently verify relevant information and seek professional advice before making property or leasing decisions.
Article contributed by Jerry Wong.
Jerry Wong is a realtor at Propnex Realty, bringing a rich background in interior and lighting design to his work. He loves exploring diverse spaces and observing the transformative power of real estate. Beyond his professional role, Jerry finds his greatest fulfillment in connecting people with the right properties, gaining immense satisfaction from helping clients achieve their dreams.
