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September 23, 2025Journal of Manufacturing Technology Management12 citations

The human side of AI adoption: exploring technostress, training and employee well-being in manufacturing SMEs

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MFMingyue FanSSSanam SoomroSSSafia Soomro

Key Points

  • A positive relationship exists between technical capability and artificial intelligence adoption in manufacturing SMEs.
  • Technostress negatively impacts both artificial intelligence adoption and employee well-being when adopting new technology.
  • Training programs are essential to alleviate stress and boost the overall success of AI adoption initiatives.
  • The study highlights a human-centered approach to AI adoption that improves job satisfaction and organizational performance.

Abstract

Purpose This study aims to investigate the relationship between technical capability (TC), technostress (TS) and employee well-being (EWB) on artificial intelligence adoption (AIA) in manufacturing small and medium-sized enterprises (SMEs). It examines the mediating role of the AI adoption and the moderating effect of training (TR). Design/methodology/approach The study used a cross-sectional survey among SMEs employees to test the proposed hypotheses. The data were analyzed using structural equation modeling. Findings The results indicate a positive relationship between TC and AIA; however, TS is found to have a negative impact on AIA and EWB. AIA partially mediates between TC, TS and EWB. Furthermore, TR is crucial to mitigate the negative impact. These findings highlight the importance of technical TR programs to alleviate stress and improve the overall success of AIA in manufacturing SMEs. Practical implications The findings indicate the importance for manufacturing SMEs to invest in TC and TR efforts that can reduce TS. By taking care of the well-being of employees and preparing them for AIA, manufacturing SMEs can develop a more resilient and efficient labor force through a human-centered approach to AIA, alleviating stress, increasing job satisfaction and improving organizational performance and EWB. Originality/value The present study builds on affective events theory by AIA and AI TR as important predictors of EWB in the digital age. It emphasizes human-centered approaches to the manufacturing technology management involving AIA.

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Cite This Study

Fan et al. (2025) studied this question.

synapsesocial.com/papers/68d4724731b076d99fa6ab18https://doi.org/10.1108/jmtm-02-2025-0120
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