What Are Germany’s Greatest Strengths When It Comes To AI?

On 2nd December, we launched the publication of our second AI study digitally (available for download here). There to discuss the current state of AI in Germany were Dr Alexander Hirschfeld from the German Startups Association; the head of hubraum, Axel Menneking, the Managing Director of the German AI Association Vanessa Cann, plus Maria Meier, the founder of the AI startup Phantasma and Professor Dr Jürgen Seitz.

Couldn’t make it? Don’t worry, we’ve got you. Here were some of the best moments from the discussion, roughly translated into English.

As Dr Hirschfeld noted, AI is becoming increasingly central for the startup ecosystem: 43% of the startups we surveyed stated that artificial intelligence was either important or very important for them. This is encouraging! AI startups tend to be ambitious and focused on growth: for example, 35% of exit-focused AI startups see an IPO as likely for them. Research is key: startups with close ties to universities and research institutes account for 33% of AI startups and 41% of AI startup founders meet each other at university or college.

This said, there are plenty of challenges facing AI in Germany. One key issue, according to Dr Hirschfeld, is that of data and of securing open data: only 36% of AI startups stated that they have adequate access to relevant data, while 77% of German AI startups would like to see better access to open data. 52% consider the European data protection regulation a disadvantage in terms of staying internationally competitive.

A second challenge is posed by diversity: while AI startups boast a more international team (both in terms of founders and the workforce) than the average startup, women are particularly poorly represented in the sector: just 12% of AI startups are founded by women (compared to 18% of startups in general) and just 29% of the workforce in AI startups are women (compared to 38% of the average startup workforce). Since AI products and services reflect the unconscious bias of their developers, it’s particularly crucial for this sector to have a labor force that broadly represents society as a whole.

Finally, “There’s no lack of funding in Germany. But there’s a certain reserve when it comes to strategic investment and VC investment in the AI sector.” Dr Hirschfeld suggested that the sort of funding that’s available in America ($71 per head in 2020 compared to Germany’s $7 per capita) is what Germany should be aiming for if they want to remain competitive in the sector on the world stage.

CORPORATE EVENT: AI Study Release @ hubraum Campus, Berlin Berlin, 30.11.2021

A panel discussion was held, with our experts fielding questions from the audience. Here were some of the best bits:

What’s it like founding an AI startup in Germany?

Maria: I’m a first-time founder and I was surprised by how bureaucratic it was to register a startup, the fact that I had to go to a notary — and these issues apply to startups in general, it wasn’t because I was founding an AI startup. One thing I found surprising was how time consuming it was to access investment — you always read about startups scoring huge amounts of money in the papers and it gives a bit of a false impression as to how easy it is. I have a lot of acquaintances in England and it seems much easier there for startups, both in terms of administration in setting up a startup and also in terms of accessing investment.

What are the biggest problems for those founding AI startups?

Vanessa: Maria’s example is very representative because it can be difficult to get financing. The situation is improving thanks to various programs being set up to address this but once you go to VCs, there’s a real culture gap. European VCs have often never founded a startup themselves and as such, are very focused on wanting to look at the business plan, wanting to know how good the AI is, wanting to be reassured that the tech is at 100% and there are no errors. If you work in the AI world, you’ll know this is unrealistic — it can take years to ensure the tech is error free. Investors want to invest in startups that are safe bets, but obviously if such a startup existed, everyone would invest in them. It can be difficult to secure investors from the seed funding stage onwards.

Are there specific advantages for AI startups posed by being based in Germany?

Vanessa: There are various advantages – one obvious example is research, even when researchers here don’t necessarily have this mindset of wanting to founding a business or startup on the basis of their research. There’s also the proximity those in Germany enjoy to internationally recognized research institutes. Then there’s the fact that we have a very strong economy. There’s a lot of big corporations like Deutsche Telekom, “Made in Germany” is still a stamp of quality and this helps startups. However, processes can be very slow here which isn’t ideal for startups and there’s difficulty with data, which matters, because data is the new oil! We need some sort of information campaign for legal clarity and clarity in general about what data can be used.

What did you find striking about our AI study?

Axel: I was particularly enthused by the ambition [revealed in AI startups here]. When you meet or work with American founders, you recognize there’s no limits for them, they want to change the world, they have no competition in terms of their ambition. They inspire me! So this was good to see. I’m also pleased by how AI startups here are so conscious of their ethical responsibility and recognize this as an important aspect of the sector. Obviously, this sense of responsibility has to be balanced with a consideration of how fast the USA and China are working on their AI. So it’s important to find a balance, both on a national and European level.

Balance is an important topic in the study. Alex, what’s the most suprising aspect of the study?

Alexander: When we look at growth in terms of employees and other indicators, companies grow faster in non-AI sectors and this is due to a lack of investment. There’s a potential here that isn’t being realized. We interviewed AI startup founders and there are still challenges, especially with funding and regulation and even double regulation in the AI sector. A big problem for small startups is how they can fulfil all of this: Where does the data I’m using come from? How can I be sure data is discrimination free? How can I tick off all these obligations when I’m part of a startup that’s just me and one other person and I’m dealing with all the other challenges that face a small startup?

What’s the leading university in Germany when it comes to AI?

Vanessa: It depends what you’re looking for, but we can all agree that universities are a great tool for sourcing talent. Those studying IT are often more competent than those who’ve been working in the sector for a while because cutting-edge tech is being taught at these unis. We have very strong technical universities: TU in Munich, KIT, RWTH, even Berlin. Great ecosystems are developing out of technical universities.

If you want to dive deeper into the release event, you can watch the recording here:

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