Artificial Intelligence and the Selection Process of International Managers: A Case Study

Abstract

Artificial Intelligence (AI) tools are becoming easier and easier in terms of practical implementation, enabling them to be used in many new areas, including the selection of international managers based on their international experience. The selection of personnel in an international environment is a challenge that has been the subject of heated debate for decades, both in practice and in theory. Wrong decisions are cost-intensive and possibly contribute to economic failure. The aim of the present study was to test machine learning algorithms - as sub-disciplines of Artificial Intelligence (AI) - on a low-coding basis. For this purpose, a fictitious use case with a corresponding data set of 75 managers was generated and its applicability in relation to personnel selection for an international task was tested. The results show that with very little programming effort, the ML algorithm achieved an accuracy of over 80% when selecting suitable managers for international assignments - based on the international experience of this group of people. The linear discriminant analysis has proven to be particularly suitable. Both the training and validation data provided values above 80%. Keywords: Artificial Intelligence, International Experience, Manager, Machine Learning