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3 Questions for…Dr. Tobias Abthoff


1. AI as a definition is often misleading. How do you define AI? And what does data have to do with it?


I would say, AI describes the capability of a machine to imitate intelligent human behavior.

Data and AI are merging into a synergistic relationship, where AI is useless without data, and mastering data is insurmountable without AI. By combining the two disciplines, we can begin to see and predict upcoming trends in business, technology, commerce, entertainment, and everything in between.


2. Many companies are still in the beginning phases of implementing company-wide data strategies. And now they are talking about AI strategies. Is that something which should be handled separately?


In my experience – based on having seen the implementations of several corporatedata systems as well as AI strategies – the data strategy and AI strategy are co-dependent and cannot be separated. Very often I hear from clients that they think they first need to bring their data in order before even thinking about implementing AI.


And yes, without good data access, AI cannot really work. In fact, most of the time spent on AI is spent on processing, cleansing, understanding and contextualizing the data. However, you cannot really know what data will be needed in which form without knowing what you want to use it for. This is why strategies that handle data and AI separately mostly fail and generate huge costs.


3. Which industry is most suitable for AI? And how can you identify which business processes will be the first to go to AI?


The industry is not decisive when it comes to implementing AI. From legal, banking and insurance to healthcare, companies can benefit from the use of AI by providing customers with a better experience of their products and services.


Having said that, business processes with the following traits are most likely to be replaced by AI:


  • Repetitive

  • High data volume

  • Rule-based


Think about order processing or data handling, which are activities that are still being done by human workers in many companies. Because these tasks typically involve repetitive, high-volume, rule-based processes, they will be among the first to be outsourced to artificial intelligence.



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