How AI is shaping the future of real estate

As a result, the role of real estate assets is changing. Buildings are no longer just occupied by a single tenant but sit within a wider system, deriving their value from how well they ‘plug’ into power, data and supply chains rather than just from location and rent. There are three things these businesses need, namely real estate, power and microchips, three things that have never been in greater demand. Real estate is no longer just a backdrop to technology but a core part of it. Oxford Economics report that the number of data centres has increased fourfold since 2000, with capacity expected to more than double by 2030. I’ve written about this at greater length here.

LN: In simple terms, AI needs computing power and much of that computing power sits in a data centre. As AI adoption grows, we’re seeing strong demand for data centres and the infrastructure that supports them. Strong digital connectivity is equally important because AI tools rely on the fast movement of data between users and computing infrastructure. And as AI models become larger and more capable and adoption expands across different industries, we are also seeing a greater focus on power networks and grid capacity to support this growing demand.

Q: As AI adoption accelerates, what are the opportunities and challenges?

LN: As outlined, AI is making buildings smarter and is also creating investment opportunities across data centres, power infrastructure and digital connectivity. The associated challenges include ensuring that both organisations and buildings are ready to support AI at scale. To embed AI effectively across a business, you need the right data, skills, resources and investment, and that all takes time to develop.

There are challenges around preparing buildings too. If occupiers are increasingly embedding AI into their workflows, reliable power and strong digital connectivity becomes essential. AI might feel intangible, but it relies on very physical, tangible things: that should be a main takeaway for us all. 

MB: The opportunities for businesses include increasing margins through improved productivity by, at the simplest level, leaving administrative tasks to AI so that staff can concentrate on where they command value. It’s very clear for us at Knight Frank that technology is unlocking new service lines. Change management is always hard however. I see three main challenges for our industry.

First, we need to see the digitalisation of buildings. It sounds ridiculous in 2026, but we still see massive skyscrapers which are managed from a lever-arch file. Secondly, we must get people to use the tools and understand the benefits. People can be stuck in their ways and leaning into the AI champions in a business will be vital to bring everyone along on the journey.

And thirdly, we must make the tools so good and streamlined that people remember to use them day in and day out. I’m hopeful on this. Recently, teams have been in our European offices training staff around Copilot and what we found, to our surprise, was that older staff with 20 years or more experience of delegating tasks were often far better at setting expectations for AI tools. It proved to us that if you treat the tool as though it’s a person, and effectively and efficiently outline what you want, you’ll get far better results.