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June 8, 2026

Artificial Intelligence and the Future of Office

Colin Mackay, Research & Investment Strategy Manager, Cromwell Property Group

Navigating the narrative

Artificial intelligence (AI) has rapidly become a central theme in economic and market discourse. Commentary is polarised, with extreme views often dominating. On one end, AI is framed as a transformative productivity breakthrough. On the other, it is an existential threat to white-collar work and society as we know it. The impacts of AI adoption remain highly uncertain, and a healthy dose of scepticism should be reserved for those confidently claiming prescience.

Regardless, it is important to assess the potential outcomes and consider how the outlook for the office sector may shift if the technology becomes more powerful, widespread, and integrated. Answering this requires separating signal from noise, grounding analysis in historical precedent, and focusing on the mechanisms through which technological change affects occupier behaviour.

In our view, AI is more likely to reshape the composition of office demand than to compromise it. For investors, the path forward will involve selecting markets and asset types which occupiers continue to favour.

“Consider thou what the invention could do to my poor subjects. It would assuredly bring to them ruin by depriving them of employment.”

Queen Elizabeth I, 1580s, in relation to the knitting machine.

Source: Why Nations Fail, Acemoglu, Robinson (2012)

Lessons from history

Technological advancement has been the driving force behind many of humanity’s biggest transformations, from mechanisation and electrification to computers and the internet. And through history, commentators have predicted the end of employment.

In reality, while labour displacement occurred through each technological transition, new forms of activity were also created. The pool of jobs expanded as previously inconceivable industries and occupations emerged over time, and productivity gains drove significant economic growth and higher living standards.

AI may be the modern driver of a similar dynamic. This time, the scarce resource isn’t physical output, but cognitive power: the capacity to analyse, synthesise, and solve problems. By reducing the cost of cognition-intensive tasks, AI may enable firms to undertake more analysis, pursue more opportunities, run more experiments, and serve more clients. As with earlier productivity-enhancing technologies, the effect may be expansionary rather than labour-saving.

Chart of Global Real GDP per Capita
Importantly, technology-driven transformations have often been disruptive at the micro level – affecting individual workers and firms – but constructive at the macro level. History suggests that while the composition of employment changes through technological advancement, the quantity increases. For office markets, the implication is that the primary risk is not the disappearance of work, but the reconfiguration of which industries and roles drive demand.

“The number of jobs lost to more efficient machines is only part of the problem. What worries many job experts is more that automation may prevent the economy from creating enough new jobs.”

Time Magazine, 1961

Source: Why Are There Still So Many Jobs? The History and Future of Workplace Automation

Signal or hallucination?

But is this time different? Recent headlines have linked AI to significant job cuts across technology firms such as Wisetech, Block, and Atlassian. However, these corporate announcements require context.

While workforce reductions appear significant, they follow a period of rapid hiring during the pandemic and post-pandemic recovery. In these high-profile cases, employment levels remain materially above pre-2020 baselines even after announced cuts, suggesting the contractions may reflect a ‘normalisation’ of headcount rather than AI impacts.

Chart of Tech Firm Headcounts for Atlassian, Block and Wisetech

Broader evidence of an AI-led employment contraction is limited. At the aggregate level, labour markets remain resilient with little indication of structural unemployment¹. In the US, AI does appear to be having a negative impact on the employment outcomes of young people, particularly those entering the workforce², in occupations most exposed to AI automation. However, occupations that are augmented by AI continue to record employment growth across demographics³. Overall, AI is currently more visible in narrative than in measurable labour market outcomes.

“Intelligent machines are replacing human beings in countless tasks, forcing millions of blue and white collar workers into unemployment lines.”

Jeremy Rifkin, 1995

Source: The End of Work

Base case: augmentation over automation

In our view, the most plausible base case is that AI functions predominantly as an augmentative technology rather than a wholesale substitute for human labour. Central to this conclusion are the incentives and constraints that shape real world economic behaviour.

Firms optimise for growth, not just cost

Businesses optimise not only for cost minimisation but for output quality, growth, resilience, and competitive position. AI can reduce the cost of specific tasks, but its economic value is often highest when combined with human judgement, oversight, and contextual understanding. In practice, this favours a complementary relationship where workers become more productive, decisions improve in quality, and the scope of activity expands.

This will not be a universal experience. Some businesses, particularly those under margin pressure, may use AI primarily to reduce headcount and extract cost rather than to expand. But that response often says as much about the condition of those businesses as it does about the technology itself. Businesses don’t shrink to greatness, and contraction by weaker operators may ultimately create room for stronger firms to invest, grow, and take share.

Automation thresholds will increase

Recent academic research highlights the importance of task quality in shaping how firms deploy automation⁴. AI is likely to be adopted first in tasks where it can meet existing output quality at low risk. As these lower-value or more routine tasks are automated, human effort is freed up and reallocated toward activities that are more judgement-intensive, relationship-driven or context-specific.

This reallocation improves the quality of the remaining human-led tasks: more time and focus = better output. The quality threshold AI must then reach is increased, making it harder for further automation to occur⁵. This self-reinforcing augmentation loop sees people focusing more and more on higher value activities, in turn increasing the value of their labour.

Full delegation introduces risks

While AI can enhance productivity across a range of tasks, the case for fully delegating long, complex, or high-stakes work remains less compelling. Microsoft research finds that as task length and complexity increase, AI output quality deteriorates and document contents can become corrupted⁶. Errors compound across steps, objectives can drift over time, and inconsistencies can be difficult to detect.

Similar issues are evident in software development and cybersecurity. AI-assisted coding tools can accelerate development, but fully delegated code generation has been shown to contain more security vulnerabilities than human-written code⁷.

These dynamics reinforce the ongoing importance of human oversight and limit the extent to which full automation can be deployed. While the technology will likely improve, it will take time and resources. Productivity gains are therefore likely to be uneven and may be slower to materialise than implied by some of the more optimistic claims.

High unemployment will not be allowed to persist

At a macro level, there are social, economic, and political limits to how long high unemployment can persist without response. South Korea (late 90s) and Spain (early 2010s) are useful modern examples: in both cases, severe labour market deterioration was accompanied by social strain, political pressure and, ultimately, policy adjustment.

Elevated unemployment and the dislocation that accompanies it tend to provoke institutional adaptation aimed at restoring labour market stability. For that reason, the more plausible outcome is slower, more adaptive adjustment rather than a sustained period of mass unemployment.

Downside case: weaker demand but no sectoral collapse

A more pessimistic scenario could arise if the pace of AI-driven disruption materially outstrips the economy’s capacity to adapt. Even in that case, however, the implications for office demand are unlikely to be linear.

A reduction in labour input doesn’t necessarily require a one-for-one fall in employment. Given society’s limited tolerance for sustained unemployment, weaker labour demand would more likely be absorbed through changes in working patterns than through mass job losses. One potential mechanism is a reduction in average working hours, such as the adoption of a four-day work week. This would adjust overall labour supply while avoiding a commensurate decline in employment.

For office markets, fewer hours worked wouldn’t necessarily translate into a proportional reduction in space demand. Offices, like stadiums, are typically configured to accommodate peak occupancy (e.g. anchor days) rather than average utilisation. And in a future where the human-centric elements of work such as collaboration, innovation, and culture-building become more important than the routine, having sufficient fit-for-purpose space will be far more important than maximising workplace density.

Supply dynamics would also act as a moderating force. Elevated construction costs, tighter financing conditions and feasibility constraints are already limiting new development, reducing the risk that weaker demand outcomes translate into structural oversupply. At the same time, ongoing population growth should continue to support aggregate economic activity and space needs over time, even if AI reduces labour intensity in some functions. Over time, the withdrawal or conversion of obsolete stock would provide further stabilisation.

The chart below puts potential downside scenarios into context and illustrates that desirable stock (i.e. prime) should be relatively resilient even in the event of a severe reduction in demand. Flight-to-quality and the withdrawal of secondary assets from the market could, over time, wholly absorb a contraction in excess of 30%. Under such a scenario, investment outperformance would become increasingly dependent on asset selection and the alignment of building attributes and tenant experience with occupier needs.

“Most, if not all professional tasks…will be fully automated by an AI in the next 12-18 months.”

Mustafa Suleyman, Microsoft AI Chief Executive, 2026

Source: Interview with the Financial Times via Youtube

Implications for office markets

Employment and demand mix

Under our base case, the office-using workforce continues to grow in aggregate as productivity gains support economic expansion and population growth underpins underlying demand.

AI adoption is likely to be slower in parts of the economy where compliance, accountability and implementation constraints are more significant (e.g. government). The effects may also be slower to emerge in industries such as construction and manufacturing, where office-based roles are more closely tied to physical operations.

By contrast, back-office processing functions that are more standardised and repeatable face greater automation pressure. Even if these roles are materially disrupted, the impact on the broader Australian office market should be limited given the diversity of the domestic demand base. In some offshore markets, where these functions account for a larger share of demand, the effects could be more pronounced. In Metro Manila for example, the Business Process Outsourcing sector accounted for 64% of leasing demand in 2025⁸.

Smaller occupiers, more fragmentation

We believe AI may shift occupier demand toward smaller businesses and drive a more fragmented tenant base. Lower start-up costs and the emergence of new business models may encourage new entrants, while existing small and medium-sized enterprises are, in our opinion, more likely than large corporates to use productivity gains to support growth rather than bank the savings through cost-outs. That tendency partly reflects the more dynamic and multi-functional nature of roles within smaller organisations, which makes them less amenable to automation than the more process-oriented roles in larger firms.

Smaller occupiers are also far less able to hand back space or sublease part of their footprint, reducing the likelihood of short-term speculative contractions. This theme was evident during the pandemic and post-pandemic recovery, when smaller occupiers accounted for a greater share of net office demand and were more likely to expand than contract.

Across office markets, this would support greater demand for smaller, more adaptable floorplates that are better suited to this size of tenant, along with assets that offer attractive shared amenity such as boardroom facilities and collaboration spaces. It may also increase the value of flexible leasing structures and speculatively fitted suites, given smaller occupiers are less likely to have the internal resources to plan and deliver bespoke fitouts.

Space use and workplace design

Densification has been gradually occurring for decades, and we don’t expect AI to materially reverse or accelerate this trend. The more meaningful shift is likely to be in workplace design, as floorplates evolve away from desk-heavy layouts toward more meeting rooms, collaboration spaces, and shared amenity to support in-person interaction for complex and valuable work.

This may increase the importance of technology integration and bandwidth capacity within buildings, as occupiers place greater value on seamless connectivity and the ability to support more data-intensive ways of working. Similarly, greater reliance on AI-enabled workflows is likely to elevate data security and control considerations for some occupiers, shaping preferences toward buildings with secure, resilient technology environments.

Quality and market polarisation

These shifts are likely to make office demand less homogeneous. Firms will adopt AI at different speeds, in different ways, and with different workplace requirements. Buildings that can accommodate varied and evolving occupier needs, both through physical adaptability and management flexibility, should attract a greater premium.

Location and quality preferences are also likely to strengthen rather than weaken. High-skill, knowledge-based work will continue to benefit from agglomeration, reinforcing the role of major CBDs. As the office becomes more focused on enabling high-value work outcomes, fit-for-purpose space and proximity to key stakeholders are likely to become higher priorities relative to rent minimisation.

We expect this to result in a wider divergence between prime and secondary assets, with higher-quality buildings better positioned to capture demand and lower-quality stock facing increasing pressure from functional obsolescence.

Investment implications

Asset selection to drive outperformance

AI is likely to widen the performance gap between winners and losers, making asset selection more important. The key question for investors is not whether office demand disappears, but which buildings and precincts remain aligned with the sectors, occupiers, and workplace functions most likely to grow. Assets best positioned to outperform are likely to be those with timeless characteristics: difficult-to-replicate location, natural light, relevant amenity, adaptable floorplates, and the capacity to accommodate evolving occupier needs.

Leasing advantage to shift toward diverse occupier pools

If AI supports stronger demand from smaller businesses and creates a more fragmented tenant base, leasing advantage is likely to shift toward assets that can cater to a broader mix of occupiers. Smaller floorplates, flexible suite sizes, and buildings that appeal to a more diverse range of industries, including less traditional office users, may therefore be better placed to capture demand. By contrast, large contiguous floorplates may become less attractive if demand is spread across a wider mix of smaller occupiers and anchor tenant commitments become less reliable.

Active management to become more valuable

Operating capability will matter more in a market defined by transition and evolving occupier requirements, where fitout decisions are harder to get right and responsiveness to tenant demand becomes a greater source of differentiation. Leasing strategy, repositioning, amenity upgrades, and selective refurbishment are all likely to become more important drivers of performance. In such an environment, landlords and managers with integrated capabilities across design, project management, leasing, and delivery should be better placed to respond quickly, shape fit-for-purpose solutions, and convert demand into stronger asset outcomes.

Secondary stock will need to compete harder on price

The principal risks are concentrated in undifferentiated secondary assets and buildings that cannot adapt to changing occupier requirements. Secondary stock can still offer compelling investment returns, but is likely to face greater pressure on tenant attraction and retention. As a result, these assets may need to compete more aggressively for tenants, and acquisition pricing will need to reflect the higher degree of risk to the income outlook.

Dislocation to create opportunity

Negative sentiment around AI and office demand may create a temporary dislocation between market pricing and underlying fundamentals. If asset values come under pressure from broader market pessimism about the demand outlook, while supply remains constrained and stock withdrawal continues, attractive entry opportunities may emerge for long-term investors able to distinguish between cyclical fear and structural impairment.

Evolution, not extinction

Artificial intelligence will reshape aspects of the economy and society. Historical precedent suggests that while disruption is inevitable, labour markets adapt to technological change and new forms of demand emerge.

For office markets, the outlook is best characterised as evolutionary rather than existential. Demand is likely to become more selective, fragmented, and quality-focused. Investment performance is likely to be driven less by broad sector exposure and more by asset selection and management capability.

In our view, the assets best placed to outperform are those aligned with the needs of a more diverse and dynamic occupier base: well-located buildings with strong amenity, adaptable floorplates, fit-for-purpose space, and the flexibility to cater to smaller tenants and evolving workplace requirements.

Evaluating the Impact of AI on the Labor Market: Current State of Affairs. Gimbel, Kinder, Kendall & Lee (Oct-25)
Young workers’ employment drops in occupations with high AI exposure. Atkinson & Yamco (Jan-26)
Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence. Brynjolfsson, Chandar & Chen (Nov-25)
O-Ring Automation. Gans & Goldfarb (Jan-26)
You will comply with the AI. Ellis (Westpac) (Feb-26)
LLMs Corrupt Your Documents When You Delegate. Laban, Schnabel & Neville (Apr-26)
Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity. Cotroneo, Improta & Liguori (Aug-25)
Metro Manila office market shows strong 2025 performance. JLL (Feb-26)

Disclaimer

This material is prepared for discussion only and should not be relied upon for any other purposes. It has been prepared on a good faith basis but its contents have not been formally verified and no Cromwell entity or person accepts any duty of care to any person in relation to the information it contains. It should not be considered to be investment advice, marketing material or a promotion or offer of any Cromwell fund, product or services. Any person that wishes to invest in any Cromwell fund, product or services should refer to the relevant information or legal documents produced in relation to such opportunity before making any investment or other decisions. This document reflects the views of its author as at June 2026.

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May 22, 2026

From Growth to Income: How the Federal Budget is reshaping investment priorities

This article contains general information and commentary only. It does not constitute investment advice or a recommendation. This document reflects the views of its author as at May 2026. These observations are based on current policy proposals and market conditions, which may change.

For investors assessing portfolio allocation, the key takeaway from this Federal Budget is the broader policy shift rather than any single measure. To the extent proposed tax changes reduce the relative appeal of residential strategies that depend more heavily on tax advantages and capital growth, income-producing assets may warrant closer consideration. That may improve the relative appeal of quality commercial real estate, where returns are often supported by contracted cashflows, tenant covenants and leasing fundamentals, although the extent of that benefit will depend on how different components of return are ultimately taxed.

Portfolio strategies already shifting given macro backdrop

This reset is landing at a time when investors are already recalibrating around two dominant macro themes:

Inflation and interest rates: Markets remain sensitive to the risk of a “higher-for-longer” environment. Assets that provide a hedge against inflation may be viewed more favourably. (Related reading: Higher interest rates and the implications for unlisted property).

Geopolitics and uncertainty: When uncertainty persists, downside protection, diversification and real‑asset exposure become more important. (Related reading: Unlisted commercial property in uncertain times).

Against that backdrop, proposed Budget measures introduce additional considerations for investors, and potentially tilt preferences toward assets that are more income-oriented.

the key takeaway from this Federal Budget is the broader policy shift rather than any single measure

What changed (and why it matters for property investors)

Two measures were particularly salient for investors:

1) Negative gearing changes (residential focus)

Proposed reforms to negative gearing for established residential property may reduce the relative after-tax appeal of some residential strategies, particularly those that rely more heavily on tax settings to support returns. For investors, the key implication is comparative: if established residential after-tax outcomes become less attractive, some investors may place greater weight on other asset classes. In that context, commercial property may warrant closer consideration, particularly where return profiles are supported by income and leasing fundamentals rather than reliance on tax settings to enhance outcomes.

2) Capital gains tax (CGT)

Proposed changes to CGT may diminish the after-tax payoff from capital gains for some investors, which may increase the relative appeal of strategies supported by current income rather than purely back-ended appreciation.

However, the implications for commercial property investors are more nuanced. While proposed changes to negative gearing are focused on residential property and do not directly affect the deductibility of income from commercial assets, commercial investors may be exposed to the changes in CGT. In addition, many private investors hold commercial property through discretionary trusts, where forthcoming tax changes may further influence after-tax outcomes.

For property trusts in particular, part of the income distributed can be tax deferred, which reduces the cost base over time and can shift a portion of returns into capital gains. This means overall outcomes may still depend meaningfully on CGT treatment at disposal.

As a result, while income-oriented strategies may become relatively more attractive, any reduction in the CGT discount could still weigh on total returns for some commercial property investors, depending on structure and the balance between income and capital growth.

The impact won’t be uniform: two investors can hold the same asset and experience different net outcomes. Investors may wish to assess exposure at the structure level (individual, company, trust, SMSF, etc.) and seek advice where appropriate.

Why commercial property looks relatively stronger

Commercial real estate’s return profile is typically anchored by rental income (often with CPI or fixed escalations) – supported by:

Lease terms and WALE (weighted average lease expiry)

Tenant covenant quality and occupancy fundamentals

Asset selection and active management (leasing, retention, capex discipline)

In other words, while capital growth matters, many commercial property strategies are not primarily dependent on it.

In that context, well‑selected commercial property may play a stronger role as a portfolio income stabiliser and diversifier, particularly where cashflows are supported by leasing fundamentals and supply constraints, noting that after-tax outcomes will still vary depending on investment structure and the treatment of capital gains over time, making it important for investors to consider how their investment structure influences after‑tax outcomes. These characteristics do not remove risks associated with commercial property, including tenant concentration, leasing risk, valuation movements and changes in financing conditions.

Bottom line

The Budget doesn’t rewrite the investment case for commercial property, but it may be considered by market participants to improve its position within portfolios relative to strategies for established residential that are more reliant on tax settings and capital growth. Combined with macro conditions that elevate the value of dependable cashflows, the policy direction reinforces a simple point for investors:

In a world where growth is less advantaged and uncertainty remains elevated, contracted income and real‑asset diversification matter more.

Disclaimer

This material is prepared for discussion only and should not be relied upon for any other purposes. It has been prepared on a good faith basis but its contents have not been formally verified, and no Cromwell entity or person accepts any duty of care to any person in relation to the information it contains. It should not be considered to be investment advice, marketing material or a promotion or offer of any Cromwell fund, product or services. Any person that wishes to invest in any Cromwell fund, product or service should refer to the relevant information or legal documents produced in relation to such opportunity before making any investment or other decisions.

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April 28, 2026

Higher Interest Rates and the Implications for Unlisted Property

Recent geopolitical developments, particularly disruption to the Strait of Hormuz, have driven a sharp repricing of interest rate expectations. Financial markets now anticipate an additional 64bps of cash rate hikes this year¹, while the Australian 10-year Government Bond Yield has increased by 34bps since late February². For commercial property investors, the key question is how these changes translate into asset values, income, and risk.

The relationship between interest rates and cap rates is often simplified – higher interest rates lead to higher cap rates, and therefore lower values. While directionally correct, this framing overlooks a critical point: property markets are not driven by interest rates alone, but by how those rates reshape the broader cost and availability of capital, and supply and demand levers. It is within these interactions that both risks and opportunities emerge.

Key takeaways

Rates matter, but capital conditions matter more: what investors demand (and how much capital is available) ultimately drives pricing, rather than a fixed spread to bond yields.
Outcomes aren’t uniform: the impact of higher interest rates varies across assets, capital structures, and investment strategies.
Dislocation creates opportunity: where tenant demand remains resilient and supply constraints limit new competition, attractive entry points can emerge.

Required return: the anchor for property pricing

At a fundamental level, property yields are anchored to the risk-free rate, typically represented by long-term government bond yields. Investors require a premium above this base rate to compensate for the additional risks inherent in property, such as illiquidity, leasing risk, and asset-specific factors.

In simplified terms, cap rates can be understood as the sum of the risk-free rate and a risk premium. When bond yields rise, the required (or target) return also increases, placing upward pressure on cap rates and downward pressure on values. This relationship isn’t unique to property – all asset classes are priced relative to the risk-free rate and face similar value adjustments.

However, this relationship is not mechanical, and the risk premium embedded in cap rates is not fixed. It expands and contracts depending on market conditions, rent growth expectations, investor sentiment, and capital flows, and may move sharply or gradually, immediately or with a lag. The chart below highlights this variability in the spread between bond yields and property cap rates over time, using Prime Brisbane CBD Office as an example.

Importantly, it shows that the current spread is consistent with the long-term historical range, despite the recent increase in bond yields. The decade leading into the pandemic exhibited a wider yield spread, however this period was defined by below-trend economic growth and unprecedented monetary intervention.

Quantitative easing suppressed government bond yields³ to anomalously low levels, and pricing relationships observed during this period are unlikely to represent a sustainable long-term baseline. The chart also shows that periods of negative spread can occur when robust rent growth is expected.

Cost of debt: asset and vehicle-level impacts

While required returns determine what assets should be worth, the cost of debt plays an important role in both the ongoing performance of leveraged assets and the prices buyers are able to pay.

For existing investments, higher interest rates – to the extent they are unhedged – increase borrowing costs, reducing net income and, in some cases, distributable earnings. The degree of impact varies materially depending on capital structure, hedging, and refinancing profiles, with assets exposed to near-term repricing more directly affected.

For new transactions, higher borrowing costs reduce the level of leverage that can be supported by a given income stream. Additionally, as the spread between asset yield and the cost of debt compresses, the benefit of leverage diminishes and equity returns decline.
In practical terms, higher funding costs reduce many buyers’ maximum bids, unless they are willing to accept lower returns. This effect is often reinforced by more conservative lending conditions. As interest rates rise, interest coverage ratios compress, and lenders may respond by reducing leverage, tightening covenants, and adopting a more selective approach to capital deployment. This further constrains the availability of capital, amplifying the impact of higher borrowing costs on both transaction activity and pricing.

However, the impact is not uniform. Investors with greater certainty over funding costs, or those less exposed to near-term repricing risk, may be better positioned to transact in this environment.

Liquidity: how markets actually reprice

Changes in required returns and borrowing costs are not reflected in property values immediately or uniformly. Instead, they emerge through transaction activity, which typically slows as financial conditions tighten.

As borrowing costs rise and lending conditions tighten, fewer buyers are able or willing to transact at prior pricing levels. This reduces competitive tension and leads to lower transaction volumes.

In this environment, transactions often occur between the most motivated sellers and well-capitalised or opportunistic buyers. Observed pricing can be influenced by the specific circumstances of those participants, rather than reflecting a broad cross-section of the market.

This helps explain why property markets often adjust in stages. Valuations are typically based on a body of transaction evidence, with individual transactions assessed for relevance and representativeness. In periods of low activity, isolated trades – particularly those involving motivated or forced sellers – may not be viewed as reflective of broader market conditions. As a result, a sufficient weight of evidence is often required before pricing benchmarks are reset. Importantly, this is not a sign of market dysfunction, but a feature of how private markets absorb new information.

Income stability vs valuation volatility: a temporary divergence

One of the defining characteristics of real estate is the relative stability of its income profile. Lease structures provide contractual cash flow, and rental adjustments typically occur gradually. Valuations, by contrast, can adjust more quickly through changes in required returns. This can create a divergence, where asset values decline due to higher cap rates even as underlying income remains stable or continues to grow. For long-term investors, this distinction is critical – valuation adjustments can create opportunities to acquire quality assets with robust fundamentals at more attractive pricing. It also reinforces the need to look beyond headline yields and focus on risk-adjusted returns across the entire investment hold period.

From adjustment to opportunity

Periods of rising interest rates are often accompanied by uncertainty and volatility. However, they can also present compelling opportunities for investors.

As highlighted in our previous article, the balance of supply and demand is the biggest driver of unlisted property performance over the long-term. The supply outlook for most property sectors was already significantly constrained heading into 2026, and recent inflationary pressures and interest rate changes linked to the Middle East conflict are likely to further limit new project commencements. For well-located existing assets with resilient tenant demand, this dynamic supports the medium-term outlook.

Risk-off sentiment and attractive entry pricing also create a more constructive environment for capital deployment. For investors with a long-term perspective and a disciplined approach to asset selection, dislocations between fundamentals and sentiment may enable the acquisition of quality assets below fair value.

As markets recalibrate, the focus shifts from navigating volatility to selectively capturing value. In that transition, the foundational drivers of unlisted property performance – income, asset quality, and long-term space market fundamentals – remain central to long-term investment outcomes.

1. ASX, as at market close 2nd April 2026
2. MarketWatch, as at market close from 27th February 2026 to 7th April 2026
3. Why Are Long-term Bond Yields So Low?, RBA (May-19)

This document has been prepared by Cromwell Funds Management Limited ABN 63 114 782 777, AFSL 333214 (CFM) and Cromwell Property Securities Limited ABN 11 079 147 809, AFSL 238052 (CPSL), both of which are wholly owned subsidiaries of Cromwell Corporation Limited ABN 44 001 056 980; and Cromwell Real Estate Partners Limited ACN 152 674 792 (CREP) as trustee for the Cromwell Creek Street Investment Trust. All statistics, data and financial information are prepared as at 31 December 2025 unless otherwise indicated. All dollar figures shown are in Australian dollars unless otherwise indicated. While every effort is made to provide accurate and complete information, Cromwell does not warrant or represent that the information is free of errors or omissions or is suitable for your intended use and personal circumstances. Subject to any terms implied by law that cannot be excluded, Cromwell accepts no responsibility for any loss, damage, cost or expense (whether direct or indirect) incurred by you as a result of any error, omission or misrepresentation in the document. This document is not intended to provide investment or financial advice or to act as any sort of offer or disclosure document. It has been prepared without taking into account any investor’s objectives, financial situation or needs. Any potential investor should make their own independent enquiries, and talk to their professional advisers, before making investment decisions. Past performance is not a reliable indicator of future performance. In particular, distributions and capital growth are not guaranteed. Various unlisted funds are referred to in this document. At the date of this document, the funds are not offered outside of Australia and, in some cases, New Zealand. Neither CFM nor CPSL receive any fees for the general advice given in this document. Cromwell Property Group (Cromwell) comprises Cromwell Corporation Limited ABN 44 001 056 980 (CCL or the Company) and the Cromwell Diversified Property Trust ARSN 102 982 598 (DPT or the Trust), the responsible entity of which is CPSL.

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November 27, 2025

Tracking the office recovery – five charts that tell the story

Colin Mackay, Research & Investment Strategy Manager, Cromwell Property Group

After a 19-year premiership drought, the Broncos have returned to the top of the rugby league totem pole. Another redemption story, not as long in the making, is underway in commercial real estate. Office was out of favour through the pandemic, weighed down by rising interest rates, subdued liquidity, and concerns that remote work would irreparably damage demand for space. Now, conditions are improving and sentiment is becoming more positive – and the proof is in the total return pudding. Below are five charts that highlight the recovery occurring in the office sector.

1. Asset prices appear to have bottomed

Office asset values across Australia fell -18% from late 2022 to the end of 2024. The devaluation cycle appears to have concluded, with appreciation of +1.2% recorded over the first half of 2025¹ . The downturn has created a compelling entry point for investors – office is currently providing a larger yield premium over the Australian 10-year Government Bond compared to the 30-year average.