Motivations and Dynamic Capabilities Influencing Employees’ AI Learning Willingness
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This study investigates the factors influencing employees’ willingness to learn AI by examining the roles of intrinsic motivation, extrinsic motivation, and individual-level dynamic capabilities (sensing, seizing, and reconfiguring). Drawing on self-determination theory and dynamic capabilities theory, data from 350 Taiwanese employees were analyzed using PLS-SEM. Results show that both intrinsic and extrinsic motivations significantly enhance AI learning willingness, with the model explaining 56.4% of the variance (R² = 0.564). Additionally, all three dynamic capabilities positively impact both types of motivation, underscoring their foundational role in employee readiness for AI. A multi-group analysis revealed no significant moderating effect of job type (technical vs. non-technical), suggesting that motivational drivers for AI learning are consistent across different occupational roles. These findings contribute to the theoretical integration of motivation and capabilities in technology adoption and offer practical guidance for developing inclusive, motivation-based AI upskilling strategies in the workplace.
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