Like most of real estate, JLL is deeply focussed on how artificial intelligence will shape the built environment.  

There are many dimensions to AI's impact, from wide-angled perspectives on changes to the global economy, to the implications on corporate talent and productivity. At the individual level, it is estimated that over 1.3 billion people have used AI, with 88% of corporates now regularly using AI to provide enabling tools for new and better solutions to many of life's needs, according to McKinsey & Co. 

At the city level the effects will be nuanced, uneven and profound.  

There is a direct relationship between the $3 trillion global AI infrastructure investment supercycle and the cities that will see the most significant benefits. The $1.2 trillion allocated to data centre (DC) investment depends on the energy solutions that will power them.  

For Large Language Model (LLM) training, reliable energy connections are the critical driver of DC location. But, inference (ie the use of AI, instead of training AI) requires low latency, so this DC capacity must be located as close as possible to the markets with the largest AI demands. JLL estimates that capacity for inference computing demand will overtake LLM training requirements in 2027 and together AI workloads will double by 2030.  

This means that DC investment, and the power it requires, is highly biased towards the world's commercial capitals. And yet, despite the unprecedented capex spend on the supply side, it is not keeping pace with demand requirements.  

Businesses in these markets will attract and retain top talent on the promise that employees will have access to this fast, high volume computing power. As demand for AI compute continues to surge, consumption will focus on specific locations in specific cities around the globe.  

In London, the implications for take-up have been profound. AI firms accounted for over 300,000 sq ft of new lettings in Q1 2026 and by the end of May the total for the year stood at 614,000 sq ft. This compares with barely 200,000 sq ft for all of 2025 combined. Notably, 85% of this space was across the ‘Innovation Arc’ from Fitzrovia and Euston/ King's Cross to the City. 

The geographic footprint for the architects of the new knowledge economy is becoming clearer. 

Across the world, cities are assessing the location needs of this technology revolution, and the drivers are in fact deeply human. Innovation geographies rely on attracting and retaining talent and the connectivity within the location once there. Alongside capital liquidity and other factors, these location characteristics only fully come together in a small number of cities around the world.  

AI firms are largely 5 days-per-week employers, recognising that high cadence, high-quality workflows demand a culture of interaction that is best achieved through face-to-face interaction. They employ skilled labour and will anchor the new knowledge economy workforce. 

One of the challenges for real estate is that the 'K-shaped' demand for offices space from AI firms has been met by a mid-cycle nadir on supply. We just can't build new buildings fast enough, while AI firms typically also seek turnkey, flexible solutions. Despite the acute prime office shortage in London, the overall market scale means that firms are finding space solutions somewhat more effectively than in competitor markets. 

Strong demand from AI firms represents a big opportunity for the gateway cities of the world. London is finding solutions in a globally competitive field to take advantage of perhaps the most profound economic shift of a lifetime. Our job in the built environment is to continue to find place-based solutions for this sector to flourish.