Europe has no shortage of AI ambition. The research is world-class, the founders are technically brilliant, and the investment is flowing. And yet, when it comes to turning that potential into scaled, real-world impact, something keeps getting lost in translation.
Martin Schilling has a few ideas about what that something is and regulation isn’t at the top of his list.
There’s significant discourse critiquing Europe’s AI innovation, saying it’s due to overregulation. True or not, what’s actually happening?
Schilling: “The ‘overregulation’ argument is too convenient. It’s a partial truth, but not the root cause.
What’s actually happening is that Europe is strong in science and increasingly strong in early-stage innovation, but weak in execution at scale. Regulation becomes the scapegoat because it’s visible. Execution gaps are less visible but far more decisive.
If you look at AI in Europe, we produce world-class research and highly technical founders. But when it comes to translating that into scaled deployment, into real products embedded in industry, we slow down. That’s not primarily because of regulation. It’s because decision-making is fragmented, ownership is unclear, and companies often optimize for compliance instead of outcomes.
The US has regulations too. The difference is that they move first, then regulate. Europe often tries to define the perfect framework before moving and that costs time.”
If “unclear ownership” is a blocker, who should own AI execution in Europe – and why hasn’t this happened yet?
Schilling: “AI execution should sit at the top of the organization either C-level or directly accountable to the board.
AI is not an IT project. It’s a transformation of how a company operates, makes decisions, and generates value. If it’s buried three layers down in a data team, it will never scale.
Why hasn’t this happened? Two reasons:
First, organizational inertia. European companies are often structured in silos, IT, operations, strategy, and AI cuts across all of them. That creates ambiguity, and ambiguity kills ownership.
Second: risk culture. AI deployment involves uncertainty, and many European organizations are still more comfortable managing risk than taking it. So ownership gets diffused instead of concentrated.
The companies that are getting it right treat AI like they treated digital transformation 10–15 years ago: as a CEO mandate, not a side project.”
When you scale AI from pilot to production, what does “operational discipline” actually look like?
Schilling: “This is where most companies fail. Operational discipline means moving from experimentation to repeatability. In practice, that comes down to three things:
First, clear use-case prioritization. Not 50 pilots, but three that matter commercially. You need a direct line to revenue, cost reduction, or risk mitigation.
Second, integration into core processes. If AI lives in a sandbox, it’s a demo. If it’s embedded in supply chain decisions, underwriting, manufacturing, or customer operations that’s production.
Third, accountability with metrics. Every AI initiative needs a clear KPI: margin improvement, cycle time reduction, error rate decrease. If you can’t measure it, it won’t survive budget cycles.
At Deep Tech Momentum, we see this pattern repeatedly: the bottleneck is not model quality, it’s organizational readiness to absorb and operationalize the technology.”
If Europe doesn’t need fewer rules but clearer targets – what would a clear target actually look like? Perhaps name one or two.
Schilling: “Europe needs mission-level clarity, not just frameworks.
Two examples:
- One: ‘50% of industrial enterprises deploying AI in core operations by 2030.’
That’s measurable. It forces action across sectors like manufacturing, energy, and logistics where Europe actually has an advantage.
- Two: ‘€100 billion in deployed deep tech capital into real-world applications.’
Not committed capital but deployed. That shifts the focus from announcements to execution.
At Deep Tech Momentum, we’ve defined similar targets because ecosystems move when there’s a shared, measurable ambition.
Without targets, regulation becomes the strategy. With targets, regulation becomes a tool.”
You’ve seen European companies raise capital across fragmented markets. How does that fragmentation kill execution in practice?
Schilling: “Fragmentation slows everything down and speed is the one thing you don’t have in AI. In practice, it shows up in three ways:
First, fundraising complexity. Instead of one deep capital market, founders navigate multiple smaller ones, different legal systems, investor expectations, and ticket sizes. That costs time and dilutes focus.
Second, go-to-market friction. Expanding from Germany to France to Italy is not like expanding from California to Texas. Different regulations, procurement systems, and customer behaviors create friction at every step.
Third, lack of scale partners. In the US, you can land one enterprise customer and scale nationally. In Europe, you often need five or ten to reach the same scale and each comes with its own integration effort.
The result: European companies spend more time coordinating than executing.
This is exactly why platforms like Deep Tech Momentum exist – to compress that fragmentation by bringing founders, investors, and corporates into one marketplace where decisions can happen faster. The flagship DTM26 summit is happening on May 20-21 in Berlin.“
About DTM
Deep Tech Momentum (DTM) is Europe’s leading marketplace for deep tech and AI innovation, bringing together founders, investors, corporate leaders, and policymakers. Held annually in Berlin, the event convenes over 3,000 senior decision-makers across sectors including AI, energy, defence, manufacturing, space, and advanced materials.
Through curated programs such as investor matchmaking and corporate-startup partnerships, DTM has facilitated over €500 million in investments and hundreds of collaborations — driving innovation and technological sovereignty across Europe. DTM aims to power Europe’s next deep tech renaissance by unlocking €100 billion in additional investment and enabling 10,000 startup-industry partnerships by 2030 — strengthening Europe’s competitiveness and resilience
See Also:
Deep Tech Momentum 2026: Driving the Commercialisation of Deep Tech in Europe
