If you want to take a look at the factory of the future, you don't have to be a time traveler - a trip to Amberg is enough. There, the Siemens electronics plant sets standards for the digitalization of production: it not only choreographs the collaboration of people, machines and robots with Industry 4.0 solutions. Comprehensive networking of all products and machines also ensures that the products control their own production. This is all monitored in real time - as the really important data is always available, the team can react very quickly to deviations and use the information to improve products and processes.

However, this high level of Industry 4.0 maturity can still be increased. In the future, technologies based on artificial intelligence will support the Amberg plant team in understanding the production processes even better. The goal of achieving zero-defect production with artificial intelligence is the next milestone. It is worth keeping an eye on the company's next steps and experiences in the use of AI, as two developments can be expected in the future: firstly, further perfection of the automation of production processes on the production line - for example using machine learning or predictive analytics. The second is the networking of production with other areas of the company in order to share information even faster and more effectively.

However, we are still a long way from AI applications that take care of everything themselves. Today, many companies only realize in concrete projects that there are as many heterogeneous fields of action as there are technology variants for the use of artificial intelligence - and that a data scientist who is familiar with machine data cannot necessarily speed up administrative processes in management with an "intelligent" chatbot. In any case, experts who evaluate existing AI technologies and test them in pilot projects are in short supply in industrial companies.

On the front line of transformation: the "AI manager"

It is already difficult to formulate a job profile - the AI disciplines vary enormously and are constantly changing. Especially as the day-to-day work is not just about the technical aspects of the topic: the use of AI sets transformation processes in motion that manifest themselves on several levels - culturally and in terms of personnel as well as processes and organization. The skills of an AI manager, who ideally reports to a CTO (Chief Technology Officer), CDO (Chief Data Officer or Chief Digitization Officer) or, in the case of the Smart Factory, the plant management, should be just as diverse.

Ideally, this "head of AI" or "AI manager" is not only responsible for the selection and implementation of AI solutions, but also assumes the role of a "cartographer of knowledge" within the organization. He or she should understand exactly which production and administrative tasks can be usefully supplemented or replaced by AI, which decision-making processes are repititive, where media disruptions break through the flow of knowledge and how the raw material of AI data - both inside and outside the organization - must be promoted.

It is obvious that this wide range of tasks is particularly important in the smart factory. And it explains why the position of AI manager requires far more than technological and business understanding. After all, dealing with AI touches on a number of ethical, cultural and legal issues for which there are still no binding guidelines or reliable best practices. The AI manager needs the skills to confidently shape such multidisciplinary discourses that transcend all departmental boundaries.