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AI integration and workforce development: Exploring job autonomy and creative self-efficacy in a global context
AI integration and workforce development: Exploring job autonomy and creative self-efficacy in a global context
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AI integration and workforce development: Exploring job autonomy and creative self-efficacy in a global context
AI integration and workforce development: Exploring job autonomy and creative self-efficacy in a global context

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AI integration and workforce development: Exploring job autonomy and creative self-efficacy in a global context
AI integration and workforce development: Exploring job autonomy and creative self-efficacy in a global context
Journal Article

AI integration and workforce development: Exploring job autonomy and creative self-efficacy in a global context

2025
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Overview
This paper explores the relationship between Artificial Intelligence (AI) integration in the workplace, cultural orientation, and its impact on job autonomy and creative self-efficacy. Our study employs a mixed-method experimental design across 480 individuals from different cultural backgrounds, specifically individualistic (United Kingdom) and collectivistic (Mexico) cultures. We evaluate how they perceive AI’s role in their professional lives. We focus on two key aspects: job autonomy, the level of control and discretion employees have over their tasks, and creative self-efficacy, the confidence in one’s ability to generate innovative ideas. Our findings revealed a significant increase in job autonomy following AI integration across all participants. Interestingly, this increase was more pronounced in the individualistic participants. Regarding creative self-efficacy, we found gender-specific impacts, with male participants experiencing a decrease, contrary to our expectations. Finally, our results supported the hypothesis that cultural orientation influences perceptions of AI, with collectivistic participants being more receptive to AI integration. These findings have significant implications for organizations integrating AI in multicultural environments. They highlight the importance of considering cultural differences in AI deployment strategies and suggest a need for culturally sensitive AI systems. The study also opens avenues for future research, particularly in exploring the role of other cultural dimensions, conducting longitudinal studies, and investigating ethical and bias-related aspects of AI in the workplace.