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AI impacts on real estate assets are expected to be multi-functional, both positive efficiency/growth as well as disruptive depending on end user demand.
- AI impacts on the labour market viewed as being an "augmenting technology"
- Office property is generally identified as the most at risk of work force impacts
- AI's effects are both positive and potentially negative for office and other REIT sectors
By Danielle Ecuyer
Challenging the negative narrative around AI disruption on labour markets
The focus on potential AI disruption and obsolescence impacts versus efficiency and growth opportunities has not yet been displaced by global economic uncertainty emanating from war in the Middle East.
The most recent spotlight has been cast on the impact of AI on real estate as well as the labour force. Both are inextricably linked, with AI having the potential to both downsize and in some instances upsize work forces, thereby impacting on demand for property.
From a top-down macro analysis, Morgan Stanley identifies, as a base case outcome, GenAI as a net labour “augmenting technology”, leading to improved productivity and real wages, albeit also disruptive in nature.
The broker has developed a dashboard to track and assess labour market dynamics across several input sources, both traditional, such as surveys, as well as AI exposure measures applying big data from the in-house thematic team.
GenAI’s impacts are the latest in a series of technological disruptions in labour markets, specifically the US. Historically, disruption could evolve over multiple decades.
The most recent disruption prior to AI, the internet, saw a faster adoption and impact on the labour force, underpinning productivity gains over what proved a relatively brief period only.
The AI phase is anticipated to be faster yet again. On balance, at this stage, the disruption appears “modest”, which may in part reflect the early stage of AI adoption.
Analysis suggests that, when adjusting for relative sector economic cycles, around 10bp, at most, has been added to the overall unemployment rate to date.
Data for the younger cohort of workers, aged 22-27 years, suggest greater possible impacts and might be considered the “canary in the coal mine”. One explanation, as proffered by the broker, is this segment has higher exposure to routine, automatable tasks within occupations.
While the macro focus suggests it is harder to identify AI-related displacement in employment data to date, Morgan Stanley explains “soft” evidence, including company announcements and earnings call transcripts, reflects a higher percentage of companies discussing AI specifically in the context of labour.
Tracking shows “displacement” mentions rising more swiftly than “job creation”.
Given markets reward management via higher stock prices around cost-cutting measures, the analysis points to possible incentives for companies to couch efficiency measures as AI-driven. Thus, transcript conclusions should be viewed as “directional” rather than definitive proof of job losses.
In a separate AI-related update, Morgan Stanley emphasises AI, like previous “general purpose technologies”, is expected to lift output per worker, notably with organisational change.
Equally, previous fears of mass technological unemployment failed to materialise, but both education and re-skilling will be critical factors.
Although not the focus of this article, probable “boom-bust” cycles are highlighted as likely, with AI infrastructure investment seen mirroring, at least in part, prior railroad and telecom build-outs, with “financial excess and volatility” viewed as likely scenarios.
Commercial property: adapt or decline
Citi and Jarden assess AI impacts on real estate via a two-pronged approach, productivity and efficiency gains versus disruption and obsolescence across sectors.
At the Citi 2026 Global Property CEO conference, AI impacts highlighted varied across real estate sectors.
Across Australian and international management discussions, the key takeaway was that office impacts, in terms of labour force reductions, are more likely in regional areas where administrative roles are concentrated.
Prime office property that is well located and offers high-quality services, particularly with greater human customer interface, is viewed as less exposed to AI disruption.
As noted by Citi, impacts to date have been limited but are expected to increase over the medium term.
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