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Where does Germany stand in the area of artificial intelligence and what should the German economy do now?

O nce again, thousands of visitors from Germany and abroad are flocking to the Hanover Fair to see German engineering know-how in the form of self-controlling robots and controlling software platforms. One core technology is machine learning, a branch of so-called “artificial intelligence”. If one believes some publications, Germany is lagging far behind in this part of modern technology. AI superpowers such as the USA or China, but also Israel or South Korea, seem to be unassailably divided, see the results of the current VDE Tec-Report 2019.

The message to German industry is clear, there is an acute need for action in this area! Such appeals can be marketed effectively in the media, but the message is unclear or even destructive, especially for German SMEs. Many entrepreneurs of established companies certainly ask themselves whether we still have a chance in this field? Or a little more optimistic, how can we provide our strategy and our products with artificial intelligence?

Orientation instead of actionism is now the order of the day

Let’s take a closer look at the status we’re talking about in the field of AI: In my opinion, it is important that we do not look at a subjective impression to assess AI development in a country, but also at quantitative factors. Cambrian made an attempt at benchmarking with various indicators on behalf of the Konrad Adenauer Foundation. His KI index is based on three factors: “general prerequisites”, “research and development” and “commercialisation”. Behind these are considerations of publications, patents, start-ups, but also infrastructural factors such as mainframes, etc. In this country comparison, Germany does not come off so badly, although there is a considerable gap to the USA, but even in comparison to China this is anything but unassailable. What is particularly striking is that all country profiles differ significantly in their characteristics. The results for Germany, for example, show a particularly high level of commercialisation. This means that Germany is often successful in translating new technologies into products.

This is precisely the strength of the German economy, a strong middle class that is flexible enough to adapt new technologies and earn money with them. In a digital world of tomorrow, it may no longer be necessary to master everything to the best of one’s ability, but rather to join forces with the right partners and to profit from this knowledge for one’s own products and services.

So the next step is to take a close look at the areas in which Germany is strongly positioned and the areas in which partnerships with other countries on AI make sense. This orientation is also very important for the companies, because especially medium-sized companies do not have the resources to try out as many things as they like.

The development and implementation of AI technology alone is not possible. Germany will develop particularly well as a location for business if it succeeds in creating an ecosystem in which AI is shaped by the interaction between business, science, politics and society. This serves above all to take away people’s worries and fears of AI and to work out the benefits for the use of AI in all areas of life.

Integrating AI into strategy and products

However, the orientation phase on the topic of AI must not lead to a standstill in the company; technological development is too dynamic for this, and for the companies this means an acute need for action in the following steps:

  1. In your industry, orient yourself on which companies are already working with artificial intelligence or are developing their first solutions.
  2. Get external support for orientation, this is in many federal states meanwhile even promoted (for example the digital pilots in Baden-Wuerttemberg).
  3. Inform yourself and understand the enormous potential that the new technology brings with it.
  4. Identify topics in which you want to experiment with artificial intelligence that matches your core competencies.
  5. Look for partners who can help you with the first steps of implementation, for example universities or other companies in your value creation network who already have some experience.

Where do you start tomorrow?

The importance of artificial intelligence is so serious that everyone, especially those with entrepreneurial responsibility, should deal with it. Ultimately, it is not a matter of starting a computer science course, but of understanding the possible uses of this technology with the help of a basic understanding. There are numerous offers for this, from books to workshops and seminars to online tutorials, in which you can participate free of charge.