KI-bedingter Technostress am Arbeitsplatz

: Eine Clusteranalyse von Arbeitnehmer:innen in Österreich und Deutschland in Marketing- und Marketing-nahen Bereichen

Abstract

Artificial intelligence (AI) has gained increasing importance in recent years, and companies benefit from a multitude of advantages. Marketing, sales, product management, and customer service are among the fields most frequently using AI. Its use also has negative consequences for employees. Some employees fear for their jobs and experience stress, while others welcome the benefits of AI technologies. Regarding the general use of technology, numerous studies have already shown that so-called technostress can be experienced, i.e., stress caused by the use of technology. The increasing use of AI raises the question of the specific extent to which technostress is experienced when using AI. Recent research has found significant correlations that show that technostress experienced through AI can lead to numerous negative consequences, such as burnout, increased intentions to quit, or lower life satisfaction. However, to the best of our knowledge, no groups of employees in marketing and marketing-related sectors in the DACH region who experience greater or lesser levels of AI-related technostress have yet been identified and segmented, which is highly worthy of investigation with regard to the negative consequences of AI-related technostress. This research gap is addressed by this study. The theoretical part consists of an examination of AI and its impact on the labor market, marketing, and employees. Subsequently, perceived AI-related technostress is examined as a segmentation criterion, and suitable sociodemographic, work-related, psychographic, and behavioral characteristics for profiling the identified AI-related technostress clusters are examined. This study conducts empirical research. For this purpose, a standardized questionnaire was developed to assess the primarily mentioned characteristics and technostress among employees in marketing and marketing-related sectors. Based on an exploratory factor analysis, five newly compiled AIrelated technostress dimensions were defined. Two clusters were identified using a twostep cluster analysis. The first cluster experiences low AI-related technostress. The second cluster experiences moderate AI-related technostress. Both clusters experience the highest technostress due to changing individual and organizational conditions. The clusters differ significantly in several characteristics: attitudes toward AI, trust in AI, burnout levels, and frequency of AI use. It is shown that the second cluster is less favorable in all of these characteristics. Additionally, the share of employees holding personnel responsibility is significantly higher in the second cluster compared to the first cluster. Further, non-significant differences are highlighted. This study offers relevant results for decision-makers and HR managers to address corresponding groups within the company and implement appropriate technostress-reducing measures

Date of Award	2025
Original language	German (Austria)
Awarding Institution	Johannes Kepler University Linz
Supervisor	Wolfgang Jonas Weitzl (Supervisor)