Alexander Thamm is the founder and CEO of Alexander Thamm GmbH [at], one of the leading consultancies in Europe focusing on AI & data to create digital products & solutions.
Alex is also a member of various political associations and organizations like the KI Bundesverband and the German Data Science Society.
He’s a pioneer in the field of AI & data and his book The Ultimate DATA & AI Guide is an Amazon bestseller.
1. What is Alexander Thamm GmbH [at]?[at] is a consultancy that implements AI and data solutions for corporate clients like DB, Daimler, and BMW since 2012. Our headquarter is in Munich and we have offices in Frankfurt, Köln, Berlin, Stuttgart, and Leipzig. Organizationally, we are divided according to so-called tribes and practices. Tribes are fixed team structures and practices represent the steps of our Data Journey. The Data Journey is our holistic consulting model, which we use to help companies generate added value from data and AI.
In addition, in our Data Academy, we offer training in numerous data-related topics.
[at] was the first company in Germany to establish a Data Science and Data Engineer trainee program, where we train our employees to AI and data experts.
2. Why did you start your own company?
Before founding [at], I did my Ph.D. at LMU and worked as a freelancer for BMW. I did research in the field of bayesian models to predict customer behavior based on technical car usage data.
It wasn’t my intention from the beginning to become a freelancer. However, it was 2008, the time of the financial crisis and there were few good jobs in my area.
Nevertheless, I enjoyed my freelance time very much, because I was working in many different areas at BMW and I could move relatively freely through the company.
At that time, it was quite unusual in such a corporation that you can work cross-functionally and jump between the teams. But this method was the key to implementing successful AI projects since the data was in different departments and systems which had to be connected.
One day, BMW approached me and asked me if I wanted to work directly as a supplier for them. As a result, I only had a few hours to set up a GmbH in order to participate in BMW’s larger tenders. Since I didn’t know what the GmbH should be named after, I simply used my own name and that’s how the Alexander Thamm GmbH was born.
3. How did you find your passion for data?
For me, Data Science has something detective-like, because you try to identify truths from data. I really enjoy solving puzzles and I’m always happy to see a machine becoming intelligent and detect patterns in the underlying data.
Furthermore, it’s also the mission that drives me, that we in Germany are catching up in the field of AI and finding our place in the world. I believe that especially medium-sized companies, which are extremely important for the German economy and our society, need AI products from Germany to remain competitive in the long run. We have great companies here that offer great products but have not yet exhausted the full potential of data.
Besides, I’m personally a big fan of smart home systems, and I use AI products such as Alexa, Siri and Co. that make my everyday life easier. I like the idea of IoT and many of my household appliances are connected to each other.
4. How do you create value from AI and data?
As mentioned at the beginning, we at [at] have developed a holistic system for our AI and data projects, the Data Journey. It consists of four steps and helps us create added value from data: Data Strategy, Data Lab, Data Factory, and DataOps.
Steps 1 to 3 are necessary before delivering a finished software product at the end of step 4. For me, putting your algorithms and models into production is the most important aspect when it comes to creating value from data and AI.
So, software development is becoming more and more important in Data Science. Of course, many companies still have analytics departments that create value with the help of statistical analyses and findings. But in my opinion, scalability can only be achieved by developing AI and data products in the form of software that people use. This software has then to be operable which needs suitable operating concepts.
5. Where do you see the challenges of AI in business?
In Europe, we still have the problem that many companies have a certain skepticism towards AI projects. As an example, we had a manufacturer of household appliances as customer who initially saw no need for AI solutions. However, we took this customer by the hand and built dashboards with simulated data to illustrate the potential of AI. We knew at the beginning that one of the customer’s pain points was recommendations based on product usage. Seeing is believing. As a result, we implemented a recommender system for recipes and called it the “Netflix of cooking”.
Seeing is believing. Many companies don’t believe what is possible with AI until they are shown a prototype with simulated data.
I like to compare our approach to the movie Karate Kid, where the karate student in training always has to polish and wipe Mr. Miyagi’s car. At first, the student doesn’t understand what this is good for, but one day he is attacked and knows these defensive movements, because he has practiced them every day.
That means you have to address the clients where they currently are. Many still fear that AI like the Terminator or Wall-E will replace their jobs. Of course, that‘s not the case and therefore we established the Data Academy to address these concerns and educate the people about AI.
Furthermore, I’m a member of the KI Bundesverband, where we discuss these issues together with politicians.
6. What invention do you hope to see in your lifetime?
What I find very exciting is the concept of Artificial General Intelligence. Even if machines can already win Go, I believe that we are still miles away from that. To achieve Artificial General Intelligence, we first have to understand how certain human phenomena like dreams and intuition work scientifically.
If you can first decipher how humans function, you can then recreate human behavior in a machine.
7. If you could switch places with the CEO of a company for one day, which one would it be?
I would like to travel to the future and see my own company in ten years. Maybe I would see many things more relaxed today. On the other hand, my future self could come to today’s company and give me a few tips.
Also, I would like to switch jobs with Elon Musk for one day, just to see how he would run my company.