A race without a clear winner
For a long time, OpenAI with ChatGPT was considered unbeatable. But this certainty is crumbling. Google counters with Gemini – multimodal, deeply integrated into existing products, and with enormous reach.
AI expert Gitta Kutyniok from LMU assesses this battle of the giants in the Munich Startup interview:
“I think this is a very interesting development. I believe it clearly shows that the AI race for large foundation models is far from decided, that it goes back and forth in this sense, and that major giants keep presenting new models.”
This dynamic fundamentally changes the market. Instead of a dominant player, a fluid balance of power emerges – and that’s precisely where the opportunity lies for Munich AI startups.
When the giants fight, gaps emerge
Sebastian Flick, co-founder of Munich startup Branchly, is closely monitoring this development:
“All in all, it’s interesting to see that Gemini has caught up. In the spirit of: The Empire strikes back.”
But while Google and OpenAI try to outdo each other, they pursue a similar strategy: they build increasingly comprehensive solutions designed to cover as many use cases as possible simultaneously. Yet it’s precisely this approach that creates gaps for specialized providers. These niches now need to be filled. Flick adds:
“This creates a huge opportunity because the big players are fighting each other and want to build the most comprehensive solution, while specialized solutions from Germany have very good prospects here.”
The German advantage: Trust, proximity, specialization
While US corporations focus primarily on scaling, another factor plays a crucial role in Germany: trust.
“It’s about finding a trustworthy provider. And trustworthy means for many simply an accessible provider who talks to me, who takes me by the hand. Because everything is so fast-moving, companies need someone who says: No matter what happens, we’re going down this AI path together.”
says Flick, who built exactly such a trustworthy AI language tool with Branchly. Because many companies are just beginning their AI journey, they’re looking not just for technology, but for guidance.
Another advantage lies in Europe’s data landscape. While large US corporations often have only limited access to sensitive industrial data, this opens up new possibilities for local providers. Kutyniok emphasizes:
“Europe and especially Germany has a huge trove of data to tap into, for example in the automotive industry, where enormous amounts of highly relevant data have been generated over the years, which large international corporations often don’t have direct access to. And that’s where a huge opportunity lies for local providers and startups.””
In an industrially-shaped environment like Munich, this can become a real competitive advantage – provided startups seize this opportunity.
Efficiency instead of size: The second opportunity
Besides specialization, a second major field of opportunity is emerging for European startups: a deliberate focus on efficient, resource-conscious AI. While models like Gemini or ChatGPT grow ever larger and more energy-intensive, providers from Europe could deliberately take a different path. AI expert Kutyniok says:
“The second direction is more efficient, sustainable, energy-efficient models. This fits not only European values and regulations, but also economic framework conditions.”
At the same time, the market is fundamentally shifting in its logic. Increasingly less decisive is which model runs in the background. Instead, concrete utility moves to the fore. Companies are primarily interested in whether an application works reliably and delivers real added value. For startups, this means: they don’t need to compete with the resources of tech giants, but can differentiate themselves through functioning use cases and tailored solutions.
What needs to happen now
As great as the opportunities are, one central challenge remains: scaling. Especially when startups grow and need larger sums, they quickly hit structural limits in Germany and Europe. Kutyniok makes clear that there is often insufficient capital available once companies want to scale beyond a certain size. Added to this is a cultural factor: a comparatively low risk appetite additionally slows innovation dynamics in her view.
