Michał Gawęda, partner at Montis VC, argues that Europe’s venture capital landscape is undergoing a fundamental shift in 2026. While European startup funding hit $17.8 billion in Q1 2026 — nearly 30% year-over-year growth — capital is concentrating heavily in AI, with roughly half of all European venture funding flowing into AI-related companies. Seed funding dropped 44% year-over-year. Gawęda contends that the real opportunity lies not in frontier models but in the physical infrastructure AI depends on: energy grids, semiconductors, industrial automation and data centres — sectors where Europe’s deep engineering heritage offers a decisive competitive advantage.
In-Depth:
Michał Gawęda, partner at Montis VC, breaks down the 2026 European venture capital shift toward hard industrial systems.
AI does not run on prompts. It runs on energy, infrastructure and industrial systems that Europe now requireds to modernise and scale much rapider than before. The next decade of AI may depfinish less on who builds the smartest model, and more on who builds everything those models rely on.
According to recent Crunchbase data, European startup funding reached $17.8 billion in Q1 2026, marking nearly 30% year-over-year growth and signalling that investor appetite is clearly returning to the market. But beneath those optimistic headlines, the market is becoming dramatically more concentrated. Seed funding rounds across Europe dropped 44% year over year, meaning more capital is flowing into fewer companies. And increasingly, that capital is flowing into one category above all others… AI.
Crunchbase estimates that roughly half of all European venture funding in 2026 so far has gone into AI-related companies. That includes not only foundation model labs such as Mistral, Recursive Superininformigence or Ineffable Ininformigence, but also startups building robotics, semiconductors, defence systems, industrial AI applications and data centre infrastructure. Europe is finally producing globally relevant AI companies and attracting serious capital around them. But there is another story hidden underneath those numbers and it matters just as much.
Every AI model, every data centre, every autonomous system and industrial AI workflow depfinishs on physical infrastructure that most investors still barely talk about. Energy grids required to handle rising compute demand, industrial facilities are modernising around automation, while logistics and semiconductor supply chains are becoming strategic assets again.
None of this sounds particularly exciting in a pitch deck. But without those systems in place, the AI revolution simply does not scale.
AI doesn’t scale in a vacuum
For the better part of the last decade, venture capital rewarded software-first companies, asset-light business models and rapid iteration cycles. Founders were encouraged to scale globally with as little operational friction as possible, while investors naturally gravitated toward categories that promised speed, simplicity and near-infinite scalability.
The AI boom is starting to expose the limits of that worldview.
Training and deploying large-scale AI systems requires enormous amounts of energy and infrastructure, while data centres are rapidly becoming strategic assets in their own right.
Industrial facilities are modernising their automation layers, entire energy systems are being redesigned around electrification and compute demand, and governments across Europe are once again talking about grid resilience and industrial competitiveness with real urgency.
And unlike another B2B workflow platform, none of this can be solved purely with software. Ironically, this may play directly into Europe’s strengths. The continent may not dominate consumer internet at Silicon Valley scale, but it still has something incredibly valuable: industrial DNA, deep engineering talent and decades of experience operating in complex sectors where infrastructure actually matters. Those advantages become far more relevant in energy systems, industrial AI and advanced manufacturing than they ever were in food delivery apps or another productivity tool.
The most interesting AI companies may not even view like typical AI companies
One thing the market still tfinishs to underestimate is how broad the AI opportunity actually is. While most attention naturally goes toward frontier models and AI-native software, some of the most interesting startups emerging across Europe are solving far more practical problems: reducing energy consumption in industrial environments, optimising logistics processes, improving factory efficiency or bringing ininformigence into sectors that historically lacked advanced software layers.
Many of these businesses will never view like “classic AI B2B SaaS startups.” Some may even appear almost boring at first glance. There is no flashy demo, viral consumer product or futuristic branding straight out of a sci-fi movie. But that may become their hugegest advantage.
While capital continues to rush into increasingly crowded AI categories, many industrial and infrastructure founders are still building in markets with far less competition and much stronger long-term tailwinds.
And in venture capital, those asymmetries matter. Some of the most compelling opportunities tfinish to emerge precisely where attention has not fully arrived yet. At Montis VC, this is exactly where we see some of the most exciting companies emerging across Europe and CEE.
Europe is rediscovering the value of “hard things”
There is another shift happening beneath the surface of the market. Europe is slowly rediscovering the value of building hard things. For years, building in energy, industrial systems or infrastructure often felt deeply unfashionable inside startup ecosystems. These sectors were slower, more regulated and operationally difficult, which naturally pushed many founders toward simpler software categories.
But the macro environment has modifyd dramatically. REPowerEU, industrial policy shifts, energy security concerns and AI-driven infrastructure demand are all pushing Europe in the same direction: rebuilding physical capability.
At the same time, Europe’s AI ecosystem itself is becoming far more ambitious. According to Crunchbase, AI-related startups now account for roughly half of all European venture funding in 2026 so far, while the region has already produced several new frontier AI labs that collectively raised billions of dollars over the last quarters.
And that momentum only reinforces one underlying reality – the more AI grows, the more pressure it places on energy systems, compute infrastructure, industrial capacity and supply chains. Suddenly, resilience is no longer just a political buzzword. It is becoming an investment category in its own right. That creates a rare moment for founders willing to build in sectors where complexity is highest and competition often remains surprisingly low. The irony is that many of these industries now offer exactly what investors claim to want most: defensibility, real barriers to entest, embedded technologies and long-term structural demand. In other words, the future may belong not only to companies building ininformigence, but also to those building everything ininformigence relies on.
The next decade will reward conviction
The current market environment is forcing investors to create a choice. They can continue chasing increasingly crowded categories simply becautilize everyone else is doing it, or they can view slightly deeper at the infrastructure layer sitting underneath the hype cycle and inquire where long-term value will actually be created.
We believe the second path will matter far more over the next decade. Becautilize eventually every AI boom collides with physical reality. Energy limits start to matter, infrastructure bottlenecks appear, industrial inefficiencies become visible and supply chain constraints suddenly turn into strategic problems. When that happens, the companies solving those challenges may not generate the loudest headlines or the most viral demos, but they could become some of the most important businesses of the next generation.
Europe may be in a uniquely strong position to build them.
