Global real estate outlook – Edition June 2026

Global strategy update and outlook

The outbreak of conflict in the Middle East impacted oil prices, causing Brent crude to jump to nearly USD 119 per barrel at its peak in March. The ceasefire agreements provided some relief to markets, with oil prices coming back down from their highest point, but as of early May they remained elevated. The effective closure of the Strait of Hormuz has limited oil supplies and put pressure on fuel and energy prices. The impact on real estate markets will depend on the duration of the conflict and its ultimate effect on energy markets and inflation. Investors continue to face increased uncertainty surrounding the duration of the conflict. Before the conflict, we expected US inflation to have peaked; however, it rose to 3.3% in March from 2.4% in February and is likely to increase further in the short term. Compared to the period before the conflict, the 2026 US growth forecast from Oxford Economics has been lowered by 0.9 percentage points to 1.9%. The latest estimates suggest that the US economy grew at an annualized pace of 2.0% in 1Q26, up from 0.5% in 4Q25.

As well as the ending of the government shutdown, the pick-up is believed to have been driven by an increase in artificial intelligence (AI) investment and the effects of tax cuts feeding through. The Fed last cut rates by 25bps in December and has held them steady since, including at its April meeting, while it assessed the impact of the conflict. Market expectations for US interest rates have moved sharply higher, with some analysts even pricing in rate rises. However, we believe cuts could resume later in the year if hostilities end and energy markets calm. Kevin Warsh’s confirmation as Fed chairman may also sway the Federal Open Market Committee towards further cuts.

The European Central Bank (ECB) has kept its deposit rate at 2% since June 2025, suggesting an end to its rate-cutting cycle. The flash estimate for eurozone headline inflation for April 2026 was 3.0% (the highest since September 2023), following a rise to 2.6% in March from 1.9% in February. Oxford Economics forecasts that eurozone inflation will average 3.0% this year. The ECB is unlikely to be able to look through the energy shock and there are expectations it may hike rates gradually in the second half of 2026.

The Bank of England (BoE) last cut interest rates in December to 3.75%, but there are expectations that it is increasingly likely to raise rates next. UK inflation rose to 3.3% in March, up from 3.0% in February, driven by a sharp increase in petrol prices. The Bank of Japan (BoJ) held rates at 0.75% in April and we expect the next rate hike to be delayed until July, given the risk from higher inflation and lower growth. We then expect two more hikes in 2027 to a terminal level of 1.5%.

The preliminary estimate put eurozone growth at 0.1% QoQ for 1Q26, down from 0.2% QoQ in 4Q25. Since the conflict started, Oxford Economics growth forecasts for the eurozone have been lowered by 0.2%, to 0.8% in 2026, and by 0.1% to 1.5% in 2027. China’s GDP growth accelerated to 5.0% YoY in 1Q26, matching government expectations, and rising from 4.5% in 4Q25.

According to data from MSCI, after accounting for seasonal effects, global real estate investment volumes slipped QoQ in 1Q26 in USD terms, following two quarters of rises. We think that transaction activity remained on an upward trajectory in January and February, before slipping in March as the conflict started, when some investors likely pulled back. Volumes were still up 20% YoY in USD terms. After allowing for seasonal effects, volumes for offices and industrial were flat QoQ, while volumes fell across the retail, apartment and hotel sectors. Data centers remained resilient and showed growth. Investment volumes rose QoQ across the APAC region, following a weak 4Q25 (see Figure 1). In contrast, the Americas and EMEA regions experienced falls in activity, following a strong second half of 2025. Where activity goes from here will likely be heavily influenced by events in the Middle East.

Figure 1: Regional real estate transaction volumes (USD billions, seasonally adjusted, % QoQ)

Source: MSCI; UBS Asset Management, May 2026. Past performance is not a guarantee for future results.

Global real estate markets showed resilience against a volatile and uncertain economic backdrop in the second half of 2025, with select markets showing capital value recovery. However, the conflict in the Middle East may dampen this capital value recovery. The latest data from NCREIF showed that US all-property capital values increased 0.1% QoQ in 1Q26, after remaining flat in 4Q25, held up by the retail and industrial sectors. US residential capital values declined by 0.2% QoQ after showing continued resilience. Moreover, all-property total returns were 1.2% QoQ for the fourth consecutive quarter. In the UK, all-property capital values were flat QoQ, while total returns slipped to 1.3% QoQ, from 1.4% QoQ in 4Q25. Falls in residential capital values were a drag.

The AI landscape

In 2024, we published “Artificial Intelligence: What does it mean for real estate?.” At that stage, AI was transitioning from concept to catalyst and generative AI had only recently entered the mainstream. Data centers were emerging as the most visible real estate manifestation of the technology and much of the debate centered on potential: potential productivity gains, potential disruption to labor markets and potential implications for real estate.

Fast forward to today and AI is no longer just a buzzword, but a structural shift. AI is now embedded into social and political structures; companies are actively incorporating AI into their day-to-day operations; and the technology is impacting the physical landscape through data centers and power usage. However, we believe the thesis still stands that AI’s ultimate impact will depend on the speed of its adoption, the balance between job displacement and job creation, and the extent to which AI augments rather than replaces human decision making. As was the case for previous technological advances, the impacts on productivity, employment, and real estate investments may only be felt incrementally and over time.

The AI landscape has broadened significantly and this rapid development has coincided with the expansion of AI‑native firms. Indeed, ’big tech’ firms have driven overall equity market performance, accounting for a significant share of market indexes. While this has reinforced AI’s long‑term growth potential, it has also raised concerns around valuation excesses and the risk of an AI‑driven bubble, particularly where earnings have yet to catch up with expectations. Earnings reports for big tech companies for 1Q26 were generally positive, though. Many leading AI firms are also exposed to geopolitical risk through their reliance on global supply chains, advanced semiconductor exports and international demand, increasing their vulnerability to policy shocks.

AI’s contribution to GDP

AI can contribute to GDP in two ways. First, today, via demand for investment in AI infrastructure such as data centers and new software; and second, over time, on the supply side through higher productivity of workers as they adopt AI, which is expected to push up their output. Indeed, one of the key questions that investors had and still have is: how much will AI impact productivity and where will we see gains? Looking at the US, productivity growth since 2023 has been much stronger, but the evidence that AI is the main driver of this is weak. Although labor productivity growth in the US is visible, with growth rates well above the 2010–2021 trend pace, according to Oxford Economics, the correlation to breakthroughs in AI cannot be claimed as the cause.¹

Figure 2: US GDP growth by contribution (percentage points, annualized figures)

The St. Louis Fed has split out the contributions to US GDP growth, highlighting AI-related investments, including information processing equipment, software, R&D, and data centers (see Figure 2). The analysis represents AI’s contribution via capital expenditures rather than the resulting enhancements to productivity. Compared to the long-run average, AI factors appear to be currently contributing more to GDP growth, with the impact similar to that around the dotcom boom in 2000.

AI is a productivity enhancer at the task level and macro gains are likely to lag until firms redesign workflows. So far, we have not seen many transformational effects across firms, as slow adopters are currently focused on rolling out AI pilots and do not appear to have generated real financial returns by using AI to automate workflows. A review by Oxford Economics1 of large-scale representative surveys of firms, which ask about current AI use and its associated productivity gains, suggests labor productivity gains of around only 1.5%, based on hours per week saved by AI.

As productivity has arguably not increased by as much as originally expected, we think that investors should not rush to include AI in underwriting as a strong accelerant for rental growth and occupancy. That said, stronger productivity gains may yet feed through over time, and the successful adoption of AI likely presents upside potential. Overall, we think that it is important to consider AI in underwritings and its potential impact on the profitability of occupiers and their ability to pay rents.

AI and office employment

Potential labor productivity gains can be viewed as jobs being reshaped or eliminated – another key area where views on AI are divided. What are the likely impacts on labor markets?² We still expect an augmented model rather than the en masse elimination of white collar jobs. In most cases, we think that AI should automate tasks, not entire roles. Indeed, according to the Bureau of Labor Statistics, since 2022 (the year ChatGPT was released), the US has added roughly 3 million white collar jobs, a 3.5% increase, which includes management, professional, sales, and office roles, while other employment has increased by 3.0%. Similarly, US office net absorption increased in 2025, allaying fears of AI reducing office demand (see Figure 3). Although the mass unemployment scenario seems unlikely, the speed at which AI is expected to be adopted may create painful, temporary, frictional unemployment. Any shrinking in the labor force could have a negative effect on offices, but also a knock-on effect on other real estate sectors.

Source: CBRE; UBS Asset Management, April 2026. Past performance is not a guarantee for future results.

Within the labor market, entry-level roles look most exposed as they often consist of routine tasks that can potentially be automated. These roles are often the gateways to employment for youth and graduates and there is some evidence that AI is having an impact. The youth unemployment rate in the UK has risen relative to the overall unemployment rate since 2022, while in the US the gap has remained broadly unchanged, according to statistical office data. However, firms still will likely require junior talent pipelines for future skills, AI literacy and workforce renewal. We believe companies will likely need to focus on upgrading entry-level roles rather than eliminating them. A reduced intake may create diamond shaped workforces as opposed to the traditional pyramid model.
AI-driven risks are not just cyclical, but structural headwinds to office demand, as AI-driven efficiency gains are unlikely to translate into proportional demand growth in service-sector employment, which may lead to slower office-based job growth, rising vacancies, and muted rental growth over the next cycle.

Although office demand is at risk from AI-exposed sectors, office demand is increasing from AI-led firms. According to CBRE, since 2015, AI‑led occupiers have taken approximately 1.5 million sq. ft. of central London office space, with the majority of this occurring since 2022. AI‑led firms represented 34% of total technology sector office take‑up in central London in 2025, compared with just 4% in 2015. This is due to London’s deep, diverse talent pool, proximity to top universities, and international connectivity. Over the next few years, we think that demand will focus on high-quality offices. According to UBS Investment Bank analysis, as of January 2026, the most exposed sectors look to be tech, professional and business services, finance, real estate, and administrative support. In particular, legal and accounting employment and mid- and back-office functions appear to be at risk.

Geography plays a role too, with markets such as New York, San Francisco, London and Beijing likely best positioned to benefit from AI growth due to their deep, skilled labor markets, high concentration of innovation-led firms, and strong professional services presence. As companies increasingly use AI, occupier demand should evolve and will likely focus on server capacity, faster connectivity and flexibility, as well as tech-enabled and collaborative spaces with physical, digital, and cyber resilience. Markets where office buildings are positioned to meet these requirements in demand should benefit. However, we think that countries with more rigid labor markets may see slower adoption and gradual competitiveness erosion.

AI exposure in real estate

Efficiency gains and potential wage growth driven by AI could generate more housing demand for skilled workers in prime locations, including premium multifamily and co-living spaces in emerging AI employment nodes. On the other hand, any reduction in graduate employment would also likely have an impact on new housing demand as we may see a delay in independent living and a slowdown in the first-time buyer market. In the longer term, increased graduate unemployment due to AI may discourage students from pursuing university degrees and instead focus on other routes such as apprenticeships, which could impact demand for purpose-built student accommodation.

Also, with employment growth likely to diverge between skilled and unskilled employees, we may see less demand at the lower end of the residential rental market. Other AI-driven demand shifts will likely include data centers, as well as sites with access to high power capacity. The industrial sector is being impacted by AI capabilities such as predictive demand modelling for last mile facilities or robot-ready facilities.

Impacts on real estate investments

As AI is now widespread, the question has shifted from whether to adopt AI to how to convert it into a competitive advantage, and this strategic gap is widening. Companies with strong data platforms, clear roadmaps and repeatable deployment models appear to be pulling ahead. At the asset level, AI benefits for real estate look skewed towards operationally intensive sectors and large portfolios with scale and data, with less impact on passive, triple-net or low-touch assets. AI may offer opportunities for efficiencies in the day-to-day management of assets and in reducing operating and overhead costs, including smart building systems and the integration of PropTech.

For portfolio management, proprietary data and built-in AI capabilities have the potential to deliver more accurate and efficient operations, including deal sourcing, underwriting and portfolio construction. Integrating AI within the investment process, for example, streamlining workflow integration, automating tedious processes and unlocking new insights may free up time for strategic thinking, better decision making and stronger relationships.

In conclusion

AI looks set to deliver future productivity gains, the ultimate quantum and reach of which are unclear. Real estate investors may gain a competitive advantage from AI by targeting sectors and geographies that benefit from AI-driven demand shifts and integrating the technology into their operational processes. The capabilities of AI will continue to evolve. Investors should stay alert and anticipate future developments and their likely impact as best they can.

Unlisted real estate sector performance outlook

¹ Oxford Economics ‘Why AI won’t transform productivity in the near term’, March 2026.
² Technological advances which result in higher productivity and lower costs, but where overall demand for a product or service rises, is an example of Jevons Paradox.