Measuring the antecedents of employees’ intention to use artificial intelligence in the manufacturing sector
This study examines the key factors influencing managerial employees’ intention to adopt artificial intelligence (AI) in the manufacturing sector of Saudi Arabia. The paper assesses the impact of business innovation, entrepreneurial orientation, and technology orientation on AI adoption intention wh...
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| Format: | Article |
| Language: | English |
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LLC "CPC "Business Perspectives"
2025-03-01
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| Series: | Problems and Perspectives in Management |
| Subjects: | |
| Online Access: | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/21837/PPM_2025_01_Alhammadi.pdf |
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| Summary: | This study examines the key factors influencing managerial employees’ intention to adopt artificial intelligence (AI) in the manufacturing sector of Saudi Arabia. The paper assesses the impact of business innovation, entrepreneurial orientation, and technology orientation on AI adoption intention while also exploring the moderating role of leadership in these relationships. The study surveyed 314 managerial employees from 18 manufacturing companies in Saudi Arabia, representing sectors such as industrial equipment, consumer goods, and automotive production. Managerial-level participants were chosen for their direct involvement in AI adoption decisions. A cross-sectional design was used with an online survey, and convenience sampling was applied for its efficiency in gathering relevant insights from key decision-makers. Data were analyzed using structural equation modeling (SEM) with SmartPLS version 4.0. The findings indicate that business innovation (β = 0.351, p = 0.001), entrepreneurial orientation (β = 0.264, p = 0.00), and technology orientation (β = 0.435, p = 0.023) significantly enhance the intention to adopt AI. Furthermore, leadership was found to moderate these relationships positively, strengthening the effects of business innovation (β = 0.212, p = 0.00), entrepreneurial orientation (β = 0.371, p = 0.004), and technology orientation (β = 0.251, p = 0.031) on AI adoption. These results underscore the importance of fostering a culture of innovation and entrepreneurship, enhancing technological readiness, and developing effective leadership strategies to promote AI integration in the manufacturing sector. |
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| ISSN: | 1727-7051 1810-5467 |