Artificial intelligence (AI) is adding complexity to an already volatile macro environment, but its long-term impact on commercial real estate (CRE) is likely to mirror past waves of innovation—causing near term disruption while ultimately expanding economic capacity. Public markets offer early signals: U.S. listed REITs have posted one of their strongest starts in decades, with broad-based gains led by data centers, specialty, and triple net sectors, while office continues to face structural headwinds. This resilience reflects confidence in the durability of long-term leases and stable earnings, despite concerns about AI-driven shifts in labor demand.
In private real estate, AI is set to widen performance dispersion as investors gravitate toward high quality assets and markets best positioned to benefit from productivity gains. Business-driven sectors like office and life sciences may see slower hiring and space demand, whereas consumer-oriented sectors, including residential, retail, and industrial, could benefit if AI supports economic growth and incomes. Selectivity will remain essential, as even challenged sectors may exhibit pockets of localized strength. Ultimately, investment success will hinge on disciplined asset selection, market focus, and the ability to drive net operating income in an environment where fundamentals, not cap rate compression, will determine returns. This paper examines these themes more fully, offering a framework for understanding AI’s influence on CRE performance and the strategic choices now facing investors.
In our 2026 Annual Inside Real Estate Outlook we argued that if the global macro landscape feels unusually complex and disorderly, that’s because it is. We’re not imagining the heightened uncertainty - we’re witnessing multiple structural transformations colliding and interacting in real-time, creating a genuinely more complex and volatile environment than we’ve seen in recent decades.
AI was a key theme we identified as shaping commercial real estate (CRE) markets, and it has moved to the forefront of investors’ minds in early 2026. Broad adoption across industries has raised concerns about its potential to displace workers, a topic our macro strategy colleagues explored in their mid-February note, AI’s Impact on Jobs: Opportunities and Challenges, which informs our perspective on implications for real estate. Commercial real estate naturally sits at the center of this conversation, serving as a conduit for economic activity. In many ways, the future trajectory of CRE—and the potential effects of AI on specific sectors—depends on the structural changes AI may drive across the broader economy.
It is important to recognize that economists and technologists often view the trajectory of AI through different lenses. Many economists see AI as a productivity-enhancing innovation that may displace certain segments of the workforce in the near term, but ultimately supports stronger output, new industries, and evolving labor demand over time. By contrast, some technology commentators focus more heavily on downside societal scenarios, including structurally higher unemployment and broader disruption. Our view is that this represents a meaningful—though more nuanced— technological shift. As with prior periods of innovation, the adjustment may be uneven and disruptive across sectors, but history suggests that productivity gains tend to expand economic capacity and reallocate labor rather than permanently diminish it.
That said, the question of AI’s impact on CRE is complex (though entirely reasonable) and it’s unlikely anyone has definitive answers at this stage. In this environment, we recommend relying on a clear framework rather than predictions. The key remains what investors can control: driving net operating income growth. In a post-AI world, disciplined property and market selection becomes even more critical, as return dispersion is likely to widen between well-positioned assets and weaker ones. Durability of cash flows is central across both public and private, as well as equity and debt.
Public markets are historically an accurate leading indicator for private real estate in both downturns and recoveries—and our reading of both markets today suggests that this cycle is holding to that script. More importantly, public markets can also serve as an important barometer for secular shifts. With that in mind, it’s worth noting that U.S. listed REITs are off to their second best start to the year since 1999 at +10.5% and February, when AI concerns intensified, was the best February on record at +7.5%. Public equity real estate has outperformed S&P 500 by +984 basis points (bps) and the NASDAQ by +1,291bps, marking the strong relative start on record.
The rally has been broad-based, with 14 out of 18 REIT subsectors posting positive returns in 2026. Data Centers (+22.3%), specialty (+18.1%), and triple nets (+18.1%) stand out
Bottom line, not every property type has been immune to AI headlines, despite the sector continuing to perform well.
We believe the primary driver of U.S. listed REITs’ absolute and relative outperformance has been their long-term contractual lease structures, which provide earnings stability and reinforce confidence in the durability of longterm demand for the asset class.
So, what comes next? The other years that round out the top five best starts since 1999 ultimately finished up +29% in 2019, +28% in 2014, +25% in 2006, and +32% in 2004. The notable exception was 2007, when the sector began the year up +6%, the sixth-best start on record, but ultimately finished down -15.7%. The key difference, then, was that U.S.-listed REITs were coming off a +173% cumulative run from 2003–2006. Today, the sector is down -10% cumulatively from 2022–2025.
The short answer is that recent AI developments are poised to influence CRE by shaping both fundamentals and performance. We think dispersion in returns, the key theme of our 2026 global real estate outlook, will increase as the divide between well-positioned properties and others accelerates. Asset selectivity will become increasingly important, as investors and tenants focus on higher-quality properties that can fully capture AI-driven advantages. In business-driven sectors such as office and life sciences, AI may accelerate existing trends by tempering hiring growth and space demand. By contrast, consumer-driven sectors—including residential, retail, and industrial, could benefit from productivity gains and income growth, provided AI supports broader economic expansion. Sectors where AI enhances output and earnings potential should see relative resilience, while those tied to industries facing structurally higher unemployment or workforce displacement may encounter more sustained demand headwinds.
However, these are blanket statements and nuances are required across sectors. For instance, there are certain office markets and submarkets that may benefit from AI as new tenant demand emerges even as the broader office sector may face headwinds – there have been several recent major office commitments where AI tenants have signed long-term leases in San Francisco. Additionally, people need a place to live making both housing and essential retail more resilient; conversely commodity Class A apartments could suffer from higher AI driven unemployment.
We think Cushman & Wakefield’s AI Impact Barometer is a very useful tool. It covers nine categories – four of which are macroeconomic-focused and track the evolving impact of AI on the broader economy while the five other categories are key real estate sectors. Each category and its underlying indicators are color-coded based on a set of Momentum Scores that reflect the direction and pace of AI’s emerging impact on that category or indicator. Importantly, it addresses the nuance required when analyzing the impact of CRE.
From a portfolio management standpoint, the private equity model appears relatively safe in the near to medium term if for no other reason than the business operates in less liquid assets that can't be “traded” as easily as public securities. It’s harder to automate the asset management of private real estate. However, we think managing diverse portfolios for our clients will remain key to our investment thesis. This does not mean generically owning various property types but rather investing in the right property types in the right markets. Those that anticipate the impact of AI not only more broadly (by property sector), but also nuanced impact (within property sectors) will be the winners and are likely best positioned to deliver relative outperformance.
Bottom line, AI is likely to intensify the next phase of performance that will hinge on property fundamentals and effective asset management. Maximizing net operating income is critical as it will likely drive both income returns and capital returns in a higher for longer rate backdrop where cap rate compression is limited and disruption is higher than prior cycles. Structural themes will remain important, but clearing return hurdles will require a sharper focus and execution.
Footnotes
Source: U.S. FTSE NAREIT All Equity REITs, Bloomberg, as of 27 February 2026.
Source: U.S. FTSE NAREIT All Equity REITs, Bloomberg, as of 27 February 2026.
Source: U.S. FTSE NAREIT All Equity REITs, Bloomberg, as of 27 February 2026.
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Risk Considerations
Investing involves risk, including possible loss of Principal. Past Performance does not guarantee future return. All financial investments involve an element of risk. Therefore, the value of the investment and the income from it will vary and the initial investment amount cannot be guaranteed. AI companies face significant investment risks due to limited resources, intense competition, and rapid product obsolescence, making them particularly vulnerable to market volatility. These companies’ success heavily depends on intellectual property protection, which may be compromised by competitor innovations or legal challenges, potentially eroding their competitive advantage. Potential investors should be aware of the risks inherent to owning and investing in real estate, including value fluctuations, capital market pricing volatility, liquidity risks, leverage, credit risk, occupancy risk and legal risk. All these risks can lead to a decline in the value of the real estate, a decline in the income produced by the real estate and declines in the value or total loss in value of securities derived from investments in real estate. Commercial real estate (CRE) investing carries several inherent risks, including those related to the economy, interest rates, market fluctuations, high upfront costs, and tenant-related issues like defaults or high turnover. Economic downturns can lead to decreased property values and increased vacancy rates, while financing costs, insurance expenses, and potential environmental or structural problems can also pose significant challenges. All these factors and risks can impact rental income and overall investment returns. Private market investments, unlike publicly traded stocks, involve various risks due to illiquidity, lack of transparency, and higher minimum investment requirements. These risks include liquidity risk, market risk, capital risk, and regulatory risk. Additionally, private market investments often involve higher fees and expenses and may have longer investment horizons.
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