Employee Perceptions of AI-Driven Performance Monitoring: Mental Well-being and Job Satisfaction
Keywords:
Algorithmic Management, Artificial Intelligence (AI), Employees, Job satisfaction, Mental health, Performance managementAbstract
The application of AI in performance management by companies raises concerns about worker well-being. This study explores the views of employees about the effects of AI-based performance management on their mental health and job satisfaction, considering the case of an emerging economy such as Bangladesh. To collect data, the study used a qualitative research design involving semi-structured focus group discussions with 10 purposively selected participants (n=10) who are professionals in the information technology, finance, and academic fields. Thematic analysis was applied to the data in six steps. Main themes found were the following: increased fear and stress; reduced autonomy and creativity; unfairness and lack of trust; coping mechanisms; transparency and human involvement; and conditional acceptance of AI. Results show that AI provides consistency and impartiality, but due to its constant presence, it often causes algorithmic anxiety and dehumanization of employees. To use AI effectively, it is necessary to adopt strategies that guarantee human centrality and safeguard the dignity and integrity of workers. The AI-IOB model is one such strategy.
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