US artificial intelligence companies have become exceptionally good at planning for growth. They forecast compute demand years in advance, build sophisticated infrastructure roadmaps, model hiring, fundraising and product development with remarkable precision. Yet many still leave one of the biggest risks to chance, namely how they are going to operate when they arrive in Europe.
European expansion is too often treated as a real estate exercise, focused on finding an office, appointing a contractor, building the space and recruiting the team. But the decisions that determine whether an expansion succeeds often need to be made long before a lease is signed. Over the past two decades, I’ve worked with global organisations delivering workplaces across Europe, and I’ve seen the same pattern repeat itself regardless of sector. Companies assume they can replicate the operating model that made them successful in the United States and simply roll it out across Europe. The technology scales. The business often doesn’t.
Europe isn’t one market
One of the biggest misconceptions I encounter is the belief that Europe can be approached as a single destination. It can’t. Every country has its own regulatory framework, procurement model, supply chain, workplace culture and way of doing business. What works in London may not work in Paris. What makes commercial sense in Amsterdam may be entirely different in Madrid.
That’s not bureaucracy for the sake of it. It’s simply how European markets have evolved. The mistake many fast-growing companies make is assuming local differences can be solved once the project is underway. By then, the important decisions have already been made. When projects overrun, it’s rarely because the design was too ambitious. It’s because critical assumptions weren’t challenged early enough.
I’ve seen organisations identify the perfect location for a new European operation, only to discover halfway through delivery that local telecommunications infrastructure couldn’t support the bandwidth the business required. I’ve seen global specifications imported from the US that simply weren’t compatible with local construction methods. I’ve seen businesses spend months refining workplace designs before speaking to the people who understood how those markets operated.
None of those problems are difficult to solve. They’re only expensive because they’re discovered too late. The common thread isn’t poor decision making. It’s involving delivery expertise after assumptions have already become commitments.
Money isn’t always the answer
In Silicon Valley, speed is often achieved by deploying more capital. That mindset doesn’t always translate to Europe. I’ve lost count of the number of times I’ve heard people say, “We’ll just throw more money at it.” If you’ve left critical decisions too late, money quickly becomes the only lever you have left. Ironically, that’s often the least effective one.
Relationships and local knowledge matter, as does understanding how decisions are made in each market. Across much of Europe, trust will open more doors than budget alone ever will. That’s why the most successful expansion programmes don’t begin with procurement. They begin by building relationships and understanding local markets long before delivery starts.
This is where many AI businesses face a contradiction. They’re built around speed, while Europe rewards preparation. That doesn’t mean companies should slow down, but it does mean they should start sooner.
If you’re planning to open an office in Madrid in six months’ time, there’s a good chance you’ve already left some important decisions too late. If you’re thinking about opening one in two years, now is the time to start building relationships, understanding local markets and validating your assumptions. The earlier those conversations happen, the more options remain available. Leave them until the last minute and your choices become increasingly limited.
AI changes the conversation
AI businesses also face a challenge that many other organisations don’t. Their workplaces are becoming extensions of their technology infrastructure. Power availability, connectivity, data centre strategy, collaboration spaces and specialist engineering environments are increasingly interconnected. These decisions can’t be made independently.
A workplace strategy that ignores infrastructure is unlikely to deliver the operational resilience an AI business needs. Likewise, infrastructure decisions made without considering how people work rarely produce environments that attract or retain talent. The strongest organisations recognise that these aren’t separate conversations. They’re different parts of the same growth strategy.
The companies that succeed will think differently
Over the next decade, the AI companies that scale most successfully into Europe won’t necessarily be the ones with the biggest budgets or the fastest growth. They’ll be the ones that understand expansion isn’t something you buy. It’s something you prepare for. That means questioning assumptions before they become commitments, bringing local expertise into the conversation while decisions can still be influenced and accepting that Europe isn’t a market to conquer, but a collection of markets to understand.
Technology may have made the world feel smaller. Successful expansion still depends on understanding what makes every market different.
