Open Access

Julian Renner

• This bachelor thesis examines the integration of artificial intelligence into the talent management process of the medium-sized company Henke-Sass, Wolf GmbH. Against the background of the challenges of the shortage of skilled workers and demographic change, the role of AI as a potential tool for increasing efficiency and optimizing talent acquisition, identification, assessment, retention, development and departure is analyzed. This thesis includes a comprehensive literature review, a case study of Henke-Sass, Wolf GmbH and a SWOT analysis to answer the question of how artificial intelligence can be effectively integrated into the talent management process of a medium-sized company such as Henke-Sass, Wolf and what strengths, weaknesses, risks and opportunities arise. The results of the study show that AI can lead to improvements in all phases of the talent management process. This is possible in particular through the automation of routine activities, the reduction of biases and data-supported decision-making. However, weaknesses such as high costs, user acceptance problems and strong data dependency were also identified. The results suggest that the integration of AI can contribute to increasing competitiveness and opening up new markets, but requires careful planning and evaluation. Finally, practical recommendations for action are developed for medium-sized companies and Henke-Sass, Wolf GmbH. These are intended to promote the introduction of AI tools in selected areas in order to increase the efficiency and quality of the talent management process and at the same time ensure the acceptance and involvement of employees. The support of external experts can play a decisive role here. However, broad implementation across the entire process is not recommended.