Boardwave Live 2026: Five key takeaways

Three years into Boardwave's 10-year mission to make Europe the world's leading software economy by 2033, the conversation has changed.

Last year, we asked whether Europe's moment had arrived. This year, the evidence was increasingly difficult to ignore.

There are now more than 280 European companies generating over €100m in ARR. There are over 600 unicorns. AI is rewriting the economics of building software, while Europe's complexity, regulation and industrial heritage are beginning to look less like constraints and more like competitive advantages.

But momentum isn't the same as scale. And scale isn't the same as ownership.

At Boardwave Live 2026, 400+ leaders came together to ask a harder question: what will it take for Europe not just to build the next generation of technology companies, but to scale them, commercialise them and keep the value here?

Here are five things we took away from the day.

1. The proof is starting to show

Europe’s technology story is changing.

A few years ago, building a global technology company from Europe still felt like the exception. Today, the ecosystem looks very different. Entrepreneurs are increasingly choosing to build global companies from Europe, rather than seeing the US as the inevitable destination for scale.

As Bernard Liautaud put it on stage: “A few years ago, we had a handful of unicorns. Today we have nearly 700. In a few years we’ll have 1200.”

The shift isn't just about the headline numbers. It's about belief. Entrepreneurs increasingly see Europe as a place to build global companies while retaining European values, culture and headquarters. 

And the data tells an increasingly interesting story.

The new McKinsey and Boardwave report, Europe’s new AI edge? The emerging application layer opportunity, shows that European AI application funding has risen from just 11% of US levels in 2018 to 44% in the first half of 2026.

That’s €6.8bn raised in the first six months of this year alone.

The shift is even more striking in vertical AI. Funding for European start-ups building industry-specific applications has reached 67% of the US level, up from just 9% in 2018.

This is important because it points to a different kind of opportunity for Europe.

The region may not lead every part of the AI stack. But it has something increasingly valuable: deep expertise in complex industries, rich industrial data, established enterprise relationships and experience operating across heavily regulated markets.

As one global enterprise software executive put it in the report:

“When it comes to vertical software, complex environments, and deep, specific solutions, Europe can build leaders that grow and compete globally.”

The challenge now is to turn that momentum into durable global companies.

2. Europe doesn’t need to win the model race

The AI conversation has understandably focused on the enormous sums being invested in foundation models and compute.

Europe is not currently matching the US at that layer. The report puts European platform and infrastructure funding at just 4% of US levels, while the top three US model makers alone captured 85% of US platform and infrastructure funding in the first half of 2026.

Many of our panel members questioned whether it’s a race Europe even needs to participate in. 

Perhaps the more interesting question is what happens next. The fact that Europe may be dependent on US models needn’t be a problem. “Europe never had much oil, but we still produce great cars”, remarked Rothschild & co’s Co-Head of European Technology Anton Black.

As AI moves from general-purpose intelligence towards software that can actually understand workflows, operate inside enterprise systems and automate complex work, value may increasingly shift towards the application layer.

That plays directly into some of Europe’s strengths. Commenting on the idea of a “SaaS-surgence” following the "SaaS-pocalypse" of early 2026, our panel for ‘Where Europe wins: the AI opportunity’ pointed to a recovery characterised by “much stronger moats in vertical industries”. 

Around 94% of European vertical AI investment is concentrated in six complex sectors: industrial, energy and climate; defence and security; transport, mobility and logistics; legal and compliance; healthcare and life sciences; and financial services and insurance.

These are precisely the kinds of environments where generic AI struggles to be enough.

The opportunity is not simply to build another model. It is to build AI that understands how the real world works.

There is, however, one part of the equation Europe still needs to improve. As Franck Cohen put it: “We’re great at building – not so much at selling.” 

3. The AI-native company starts with the problem

That idea came through repeatedly on stage.

In ‘Transforming at speed’, Simon Walsh of OneAdvanced, Kriti Sharma of IFS Nexus Black and CARTO founder Javier de la Torre explored what it actually takes for established companies to become AI-native.

The answer wasn't simply adding AI to existing products. It was redesigning how the business works. They talked about building product capability throughout the organisation, including in the boardroom, and cultivating exceptionally curious people who can move expertise across functions. 

As Kriti put it: “My best salespeople are now my best AI engineers.”

The same principle came through in the AI-native companies on stage. Helen Murphy of Opply and Andrew Richardson of Fyxer AI argued that curiosity, autonomy and a relentless focus on the customer problem are fundamental.

As Helen put it:

“If you don’t start with the problem, you’re probably not an AI-native.”

That problem-first mindset came through elsewhere too. IQM Quantum Computers' Dr Jan Oliver Götz made a similar point from the world of quantum computing: “A feature that excites a scientist may not excite customers.” 

The report reaches a similar conclusion. Successful European AI application companies are embedding themselves deeply into enterprise workflows, rather than simply layering AI on top of existing processes.

That creates a different kind of moat: not just technology, but knowledge of the workflow, the data, the customer and the industry.

And it changes what we mean by “AI-native”. It is less about how much AI a company uses and more about whether AI has fundamentally changed how the company creates value.

4. Europe needs scale without losing its specificity

This was perhaps the biggest strategic question running through the day.

Europe has the ingredients: world-class universities, industrial strength, deep pools of talent, sophisticated financial markets and some of the world's most ambitious technology companies.

But the ecosystem remains fragmented.

The answer isn't necessarily to make Europe more like the US. It is to find ways to give European companies the scale to compete globally while preserving the specificity that makes them different.

The report identifies three choices that are already helping Europe's AI application leaders do exactly that: deep workflow integration, sector specialisation and a global, multimarket approach from the outset.

AI may actually help with one of Europe's historic disadvantages here.

Different languages, regulations, tax systems and business practices have traditionally made cross-border expansion expensive. But AI can increasingly absorb those differences into the product itself, making it easier to build for multiple markets from the start.

That changes the old European scaling equation.

Instead of treating fragmentation purely as a constraint, companies can design for it from day one – and use Europe's different markets as a testing ground for global products.

As one speaker put it during the day: “Think American. Stay European.”

5. The next AI opportunity is increasingly physical

Perhaps the most exciting discussion of the day looked beyond software altogether.

Chris Wigley, COO of PhysicsX, opened his session with a simple observation:

“Interesting things are about to happen in the physical world. And it’s about time.”

A mainstream car manufacturer can take three to five years to develop a new vehicle. Numerical simulation can take hours or days. AI prediction can take seconds.

That isn't simply about making existing processes a little faster. It changes what is possible.

Europe has an enormous amount of industrial knowledge embedded in its companies, universities and engineering communities. The report makes a similar case for the application layer, highlighting industrial data, specialist expertise and dense sector ecosystems as structural advantages.

The opportunity is to combine that accumulated knowledge with AI and compress the time it takes to design, test, build and improve things.

That matters far beyond technology.

If AI can dramatically accelerate engineering and experimentation, it could help tackle some of the biggest physical challenges ahead – from energy and transport to manufacturing and climate adaptation.

Europe may have lost ground in parts of the internet era. It may not lead the foundation-model race.

But it has something the next chapter of technology increasingly needs: an extraordinary amount of knowledge about how the physical world actually works.

And finally: the human advantage

The day wasn't only about technology.

Our afternoon workshops explored some of the less quantifiable ingredients of building great companies: emotional fluency, personal accountability, resilience and performance.

Sam Conniff's Hard As Nails challenged assumptions about masculinity and vulnerability, opening up a conversation about empathy, emotional fluency and the qualities that matter in leadership.

Dan Murray's How to Reach Your Heights asked Boardwavers to think honestly about what success means – and how much time they have to pursue it.

And in The Performance You’re Not Managing, former international athlete Jo Hopkins made the case that high performance isn't about doing more all the time, but doing the right things at the right time, with the right energy.

There was a useful reminder in all three sessions: technology may change the pace of work, but it doesn't remove the human challenge of deciding what is worth doing.

The next chapter

Three years into the 10-year mission Boardwave set out in 2023, the foundations for the next chapter are beginning to take shape.

Europe is no longer simply asking whether it can produce world-class technology companies. It is building them – and the emerging AI application layer suggests there may be a particularly European route to doing so.

The ingredients are here. The evidence is starting to accumulate.

Now comes the harder part: turning Europe's strengths into companies that scale globally, while keeping the value, talent and intellectual property that make them possible here.

The next chapter isn't about whether Europe can build. It's about how far we can go.