The Impact of Artificial Intelligence Adoption on Employee Performance in Malaysian SMEs: The Mediating Role of Work Motivation
DOI:
https://doi.org/10.53797/ujssh.v5i1.4.2026Keywords:
Artificial Intelligence Adoption, Work Motivation, Employee Performance, Malaysian SMEs, Self-determination Theory, PLS-SEMAbstract
The rapid diffusion of Artificial Intelligence (AI) under the Fourth Industrial Revolution has transformed organizational operations, yet its impact on individual employee performance remains insufficiently understood, particularly in developing economies. This study examines the effect of AI adoption on employee performance in Malaysian Small and Medium Enterprises (SMEs), with work motivation as a mediating mechanism. Grounded in Task–Technology Fit (TTF) theory and Self-Determination Theory (SDT), the study proposes that AI enhances performance both directly through operational efficiency and indirectly by strengthening employees’ intrinsic motivation. Using a quantitative cross-sectional design, data were collected from 326 employees in Malaysian SMEs who regularly interact with AI-driven tools. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the hypothesized relationships. The results indicate that AI adoption has a significant positive effect on employee performance and strongly predicts work motivation. Work motivation, in turn, significantly enhances employee performance. Mediation analysis confirms that work motivation partially mediates the relationship between AI adoption and performance, with the indirect effect exceeding the direct effect.The findings highlight that AI’s performance benefits are largely transmitted through psychological mechanisms rather than technological efficiency alone. This study contributes to the literature by integrating technological and motivational perspectives and providing empirical evidence from a developing economy context. Practically, the results suggest that SME managers should implement AI in ways that foster employee competence and autonomy to maximize digital transformation outcomes.
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