Nicole Büttner-Thiel, CEO Merantix Momentum © Vendela Jagdt, Merantix Momentum

16 February 2024

"We have to go all-in and embrace the positive potential of AI with the same vigor we apply to its regulation.”

Merantix is the world's first artificial intelligence platform dedicated to researching, building and investing in AI companies through its Venture Studio, AI Fund,  AI Campus, Merantix Momentum and AI House. Nicole Büttner-Thiel is an experienced business leader, tech optimist and economist and leads Merantix Momentum as CEO. In the past, she worked in asset management and strategy consulting, founded her own AI company and has experience in developing AI strategies for clients from various industries. For #ai_berlin, we talked about the success and outcomes of the AI House Davos, the EU’s AI Act and its potential ramifications as well as the state of the German economy when it comes to implementing AI solutions.

Hello Mrs. Büttner-Thiel, thanks for taking the time to speak to us. 2024 kicked off with the much talked about AI House Davos during the Annual Meeting of the World Economic Forum. What is your conclusion and what insights are you taking back with you?

It was a really exciting year at Davos hosting the AI house, which really got people engaged with the topic on a tangible level. One key takeaway was our collective drive to deploy artificial intelligence for direct, impactful change. There’s so much potential for AI to address pressing global issues, underscoring the importance of a unified effort. What stood out was the universal call to action – to move beyond theoretical debates on ethics to actually implementing AI solutions that genuinely enhance both societal welfare and economic prosperity. It's about creating an inclusive future where technology serves as a bridge, not a barrier, ensuring equitable advancement for all. This is a moment for us to champion, to turn our shared visions into reality, and to demonstrate how AI can be a force for good in our world.

Various AI topics were discussed in Davos. "Women in AI" is something that has always been close to your heart. What can you tell us about this session? Where do we stand today when it comes to minimizing gender bias in AI, and also the strong imbalance between women and men still existing in the tech sector?

The Women's Breakfast was a fantastic way to kick off the week. I had the privilege of moderating the session alongside some truly amazing panelists; Anna Makanju, VP of Public Policy at OpenAI, Deemah Al Yahya, Secretary-General at the Digital Cooperation Organization, and Nigina Muntean, Chief of Innovation at the United Nations Population Fund.

The conversation underscored the untapped potential of AI as an equalizer—a tool that can democratize access to opportunities and services. It’s really promising to see that, with the increased awareness about concerns of algorithmic biases, there has been, and continues to be, a lot of great work to create more inclusive and equitable AI systems, and to ensure that these technologies are a force for good and an agent of change across all sectors of society.

At the same time, there’s a lot of work to be done on gender diversity in the tech sector. This is true in hiring, but there is also a critical investment gap in women-led ventures. This gap isn't just a missed opportunity for women; it's a loss for innovation and society at large. Bridging this gap requires not just advocating for more women in STEM but also ensuring that women entrepreneurs receive the funding and support they need to drive their AI projects forward. 

On that note, I’m very proud of the Merantix ecosystem for putting their full support behind some amazing women-led teams in addition to my own. There’s a group of outstanding women founders here on the AI campus that keeps growing every year.

The EU’s AI Act was probably the elephant in the room throughout Davos: How do you see the international mood on the topic of AI and its regulation, also with regard to the German position?

This is actually a topic that I’ve written about, so I’m glad you asked! In Europe, the focus on ethical AI and stringent regulation, particularly in Germany, is commendable and essential. However, the focus can’t only be about setting boundaries; it must equally be about pushing forward with decisive action and investment. 

The transformative potential of AI to benefit society is immense, but realizing this promise requires more than cautious optimism or tentative engagement—it demands boldness and commitment. The prevailing apprehension, a tendency to 'dip a toe in the AI water,' risks relegating Europe to a spectator role in the global AI race. Such a hesitant approach undermines our ambition to lead in advancing ethical and socially beneficial AI. 

If we want to be leaders, we have to go all-in and embrace the positive potential of AI with the same vigor we apply to its regulation. This means substantial investment in AI research and development, support for startups, and a clear pathway for innovation to flourish alongside governance. Only by fully committing can we ensure AI serves as a fair, safe, and transformative force for good. Hedging bets and playing it safe are not options if we aim to have a global impact in this space - we’ve got to get our heads in the game and play to win.

How do you think the AI Act will change the AI sector in Europe, also in an international comparison?

As the first major piece of legislation on the topic, the AI Act could either become a model for other countries, emphasizing the importance of ethical considerations and consumer protections, or a cautionary tale of how to stifle innovation and economic competitiveness. So, it presents both a challenge and an opportunity.

As I've argued previously, the Act's heavy focus on mitigating risks, while important, may inadvertently dampen the innovative spirit that is crucial for the advancement of AI technologies. A purely risk-centric approach could lead to an environment where compliance takes precedence over creativity, potentially slowing down the pace of innovation.

To establish a leadership position in AI, Europe must complement its regulatory efforts with substantial investment in AI research and development, as well as support for the private sector – particularly startups and SMEs – to navigate the regulatory landscape. This dual approach would ensure that Europe not only leads in ethical AI but also remains a hub for cutting-edge innovation and economic growth. The ultimate goal should be to create a regulatory landscape that fosters innovation while ensuring AI technologies are beneficial to society. 

According to a study by the Chamber of Industry and Commerce, the use of AI in Berlin companies has doubled compared to last year. In your opinion, how far along is the economy in the use of AI?

Berlin is an exciting place, which is one of the reasons we chose to establish the AI Campus here. There's an energy and entrepreneurial dynamism that attracts talent here from around the world – and that energy is definitely present when talking about AI. That said, there's a risk that many companies encounter of jumping on the AI bandwagon without a clear plan for how it's genuinely going to add value. 

The key to avoiding that pitfall is meaningful integration. It’s great for companies to experiment with AI, yes, but with purpose. It's about learning from these trials—identifying where AI can truly make operations smarter, customer experiences richer, and products more innovative. And equally, recognizing where it might not be the best fit. This isn't about AI for AI's sake; it's about strategic, thoughtful application. 

To answer your question, the economy is off to a good start in terms of AI, or at least in terms of excitement about AI, but there’s still a long way to go. We need to harness that enthusiasm to make sure AI becomes not just a buzzword but a cornerstone of sustainable growth and success.

Is there a difference between large companies and SMEs? 

When it comes to AI, the playing field between big players and SMEs isn't quite level, but each has its own set of cards to play. Big companies have cash, data, and can afford teams that can dive deep into AI, exploring and implementing at scale. They can afford to experiment, fail, and try again, navigating the complex regulatory hoops with a bit more of a buffer. 

SMEs, on the other hand, need to be a bit more scrappy and clever with their resources. They don’t usually have the same deep pockets so they often make up for it with agility and innovation. Still, Machine Learning needs to leverage a lot of data to produce value, which requires a significant investment that many SMEs may struggle with. That, paired with the additional regulatory burdens associated with AI, makes it especially difficult for SMEs to stay at the head of the curve. 

This is especially important when considering that SMEs provide over half of the jobs in Germany and in many ways are the backbone of any country’s economy. If we want SMEs to succeed we have to act as good partners, both in the public sector and in larger corporates. We have to craft legislation that doesn’t undermine SME’s ability to compete, but rather provides the support necessary for them to navigate the regulatory environment, streamlines the collaborative process for them, and invests strategically in their long term success.

What type of clients are currently approaching Merantix Momentum and what challenges are they facing? Do you see a trend and what do you expect for 2024 in this regard?

We’re lucky enough to work with a wide variety of amazing clients at Merantix Momentum, ranging from SMEs to large multinationals across domains, though we have a special focus on Manufacturing, Health and Pharma, and the Public sector. 

But one thing is constant no matter the client’s size or sector; data is always a challenge. Not just capturing data, but connecting it, curating it and empowering teams to leverage that data. For us, we’re always focused on implementing ML solutions that drive real value for clients – you can think of an amazing potential use case for AI in an organization, but to realize it you have to get your data in order. 

Looking to 2024 there are a few big things on the radar. First, the AI Act is going to have a big impact and getting our clients prepped and ready for it is top of the agenda. Then, in this field, the technology advances so quickly that we also know that clients will need help keeping up and assessing which technologies could be a good fit for them. 

Chat GPT was only released publicly at the end of 2022, and look how far things have come from there? So it’s hard to predict what the space will look like a year from now. But we’re very excited because, especially with all of the amazing work we’re doing here in the Merantix ecosystem, we’re not just reacting to the future; we're helping shape it, making sure AI isn't just a buzzword, but a real value driver.

At Merantix Momentum, you support companies in their AI journeys. Part of that process is helping companies take their first steps in implementing AI to identify use cases and develop their AI strategy. How would you describe that process and what is your advice for companies just getting started with AI?

For companies just dipping their toes into the AI waters, identifying all the possible use-cases for AI in your organization is a good exercise, but the key is to zero in on cases that are both feasible and add sustained value. And we’ve actually developed a framework, the AI Canvas, to help with just that. It's not about casting a wide net; it's about pinpointing where AI can really make a difference for you—be it enhancing customer experience, optimizing operations, or innovating your product lineup. 

Once you've identified those focus areas - we call them ‘light-house’ cases - embrace an agile and experimental mindset. Think of it as 'learning by doing.' Start small with pilot projects that allow you to test the waters. This hands-on experience is invaluable; it not only helps you assess how well the case works, but also builds your team's AI capabilities. Once you’re confident and have worked out some of the kinks, then it’s time to ratchet up the investment and double down where you’re seeing success. 

Remember, the goal here isn't to overhaul a business overnight with AI. It's about iterative improvement, learning from each experiment, and gradually integrating AI into areas where it can provide the most value.

Merantix is a key pillar of the Berlin AI ecosystem. How do you contribute and what potential do you see for the future?

I like that you used the word ecosystem – that’s actually our entire approach, and I think that’s what makes Merantix such an exciting place. Instead of going it alone as a Venture Fund, Merantix made the very deliberate choice to foster a community – or ecosystem, our favorite word – that connects different parties that synergize organically. We bring together capital, deep AI expertise, cutting edge research and regulatory know-how in a great space that creates a very exciting and attractive environment for diverse talent from around the world. 

Honestly, there aren’t many places where you’re likely to see a bunch of start-up techies wearing sneakers and sweatshirts side by side with seasoned political veterans in full formal suits. But here at the AI campus that happens every day, and that collaborative atmosphere not only makes for an amazing place to work and host events, but also adds a lot of concrete value to the ventures. 

So when you get an investment from us, you’re not just getting the capital, you’re getting the whole package. We have a deep roster of AI experts to spar and collaborate with entrepreneurs to build ventures and products that go way beyond what any one company could do on its own. We already have a lot of great projects in the works, so going forward I’m excited to see us keep growing and tackle new sectors, broadening our horizons to truly make Berlin, Germany, and Europe a leader in the AI space.

Thank you for your time.

Rewatch all videos from the AI House Davos here.