The core question of the presentation was how AI applications can change business models. It is important to distinguish whether the core of the business model consists of an AI-based product or AI applications are used in various functions of the company (e.g. marketing, sales or production). The former in particular "suffer" from over-expectations on the part of customers that are difficult to fulfill. One reason for such over-expectations is the widespread perspective of viewing AI as a transformer. Even though AI has the potential to change areas of life permanently, it is ultimately a technology stack with a broad field of application to make our lives easier, healthier or more efficient.
AI goes hand in hand with a shift from algorithmic thinking to data-centric thinking. The companies that are particularly early to adapt their mindset accordingly and build the capabilities today to collect, store and process large amounts of data and are open to innovation will ultimately win the race.
The differences between the U.S. and Germany or the EU were also discussed. The USA as an economic area is large enough to develop its own technology markets. In Germany, this is not possible due to its size. Therefore, AI applications are developed in the context of existing industries in this country. One way out could be the European market, although difficulties also arise here due to language differences and trade barriers. Ultimately, unlike the U.S., the EU is an amalgamation of 27 individual markets. But Europe does have one advantage. Stricter data protection rules are currently being introduced in the U.S., so many companies in the U.S. must now adapt to stricter rules. European companies have already overcome this hurdle.