AI is redrawing real estate’s investment map

JLL’s latest research shows AI is changing how companies use people and space, creating new winners and risks across offices, logistics, data centres and investment portfolios.

• AI is breaking the traditional relationship between business growth, headcount and the amount of property companies need.
• 46% of investors surveyed are targeting AI-driven opportunities, while 34% are concentrating on protecting portfolios against emerging risks.
• JLL sees data centres and industrial property benefiting, while offices face a widening divide between quality assets and vulnerable secondary stock.

AI is becoming a property story

Artificial intelligence is no longer simply changing how businesses work. It is beginning to change how many people they employ, what those people do, where they work and ultimately what property they need.

That was the powerful message from Yuehan Wang, Global Research Director, Real Estate Technologies at JLL, at the 2026 SAPOA Annual Convention at Sun City.

Presenting JLL’s latest AI transformation research before joining CNN International anchor and business editor Richard Quest in discussion, Wang challenged property investors to look beyond the AI hype and understand how the technology could reshape real estate demand.

One of the biggest changes is fundamental. For decades, investors could broadly assume that as a business expanded, it would employ more people and therefore require more space.

That relationship is becoming less reliable. AI can increasingly enable companies to increase output without increasing headcount at the same rate.

As Wang explained, the historically stable relationship between output and headcount is beginning to decouple. That doesn’t mean businesses will no longer need property; it means investors will require much more sophisticated ways of forecasting demand.

AI has reached the boardroom

This is also no longer simply a technology department issue.

According to JLL’s global transformation research presented at SAPOA, 80% of AI agendas are now directly owned by boards or C-suite executives.

The questions have moved beyond how AI can make employees more productive. Companies are asking how it will affect competitive advantage, business models, portfolio risk and the assets their customers and tenants will require.

For property investors, that matters because today’s corporate AI decisions could become tomorrow’s leasing decisions.

JLL’s research also shows investors themselves are divided over how to respond.

Some 46% are opportunity-focused, looking to allocate capital towards opportunities created by AI.

Another 34% are risk-focused, concentrating on protecting portfolios and understanding where disruption could emerge.

Only 14% are essentially holding their existing conviction.

Not every property sector will be affected equally

The key word is divergence. AI is unlikely to create one uniform real estate outcome.

Industries such as warehousing, logistics, hospitality and healthcare remain heavily dependent on physical locations and frontline workers. Here, AI may be more about improving productivity than dramatically reducing property requirements.

Other sectors may consolidate operations as companies attempt to generate greater output from leaner teams. Even within technology, the picture is divided: rapidly growing AI businesses are taking space while some legacy software businesses face structural challenges.

That means investors need to stop looking only at broad sector labels and start understanding the businesses occupying their individual buildings.

Data centres and industrial emerge as early winners

The most obvious property beneficiary is data centres. AI requires enormous computing capacity and supporting infrastructure, creating strong structural demand.

JLL also sees moderate tailwinds for industrial property, driven by robotics, infrastructure, advanced manufacturing and new production requirements.

Its research shows opportunity-focused investors tend to have greater exposure to logistics, warehouses, data centres, manufacturing, infrastructure and energy and are looking to allocate further capital towards these areas.

But the most complicated story may be office property.

AI isn’t necessarily killing offices — it’s dividing them

If businesses can grow without expanding headcount at the same rate, office demand clearly faces pressure.

Yet AI is also creating new occupiers.

In San Francisco, Wang said AI companies have accounted for almost 30% of total office leasing activity since 2025, although this level of AI-driven demand remains concentrated in a handful of major global technology hubs.

More relevant to most property markets is what happens when businesses consolidate.

JLL believes this could accelerate the existing flight to quality.

Companies may occupy less space — but concentrate their C-suite, top talent and revenue-generating teams in better buildings with stronger amenities and environments that people actually want to use.

As Wang’s presentation effectively framed it, occupiers could increasingly choose better buildings rather than more buildings.

That potentially creates an even wider divide between prime, investment-grade offices and ageing secondary stock.

What should investors do now?

JLL’s presentation points to four immediate priorities.

Know your tenants better. Investors need to understand which businesses will benefit from AI and which face disruption.

Go deeper than sectors. Simply deciding to invest in technology, healthcare or life sciences is no longer enough. Investors need to understand the subsectors, occupations and individual businesses driving future demand.

Prioritise income growth and asset quality. JLL argues that income growth, rather than relying on yield compression, will increasingly drive outperformance.

Read the signals early. Property leases are long. By the time disruption appears clearly in vacancy and leasing statistics, investors may already be behind the curve.

And don’t confuse ChatGPT with an AI strategy

There was another warning for property companies themselves.

Giving everybody access to generative AI does not create competitive advantage if competitors are using exactly the same tools.

The real opportunity comes from connecting AI with a company’s proprietary data, property information and human expertise.

For real estate, that could eventually allow an asset manager to ask which buildings face upcoming lease expiries, high vacancy or rising energy costs and identify where capital expenditure should be prioritised.

But that requires something the property industry has historically struggled with: clean, structured and connected data.

The property winners will adapt first

Perhaps the most revealing moment came when Richard Quest reflected on the unusual quietness in the Kings Ballroom.

His observation was that delegates appeared simultaneously concerned by AI’s complexity and energised by the possibility that those who understand it could gain an advantage.

That may be the most useful takeaway for investors. AI doesn’t automatically make real estate a less compelling asset class.

But it could make asset selection, tenant selection and timing considerably more important.

The winners may therefore not be the investors who make the biggest bets on AI.

They may be those who understand its ripple effects earliest — and position their buildings, tenants and portfolios accordingly.

Read the full analysis in the October REImag

How will AI reshape offices, data centres, industrial property and the buildings of the future?

In the October edition of Real Estate Investor Magazine, we go deeper into JLL’s 2026 AI Transformation research, including the future of work, investment strategy, AI-powered asset management, data, automation, human oversight and what the next generation of buildings could look like.