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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM32807
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The rapid advancement of artificial intelligence (AI) technology has led to its increasing adoption by businesses, promising transformative changes across various industries. However, despite its potential benefits, many organizations are still in the early stages of AI adoption, grappling with complexities and uncertainties surrounding its integration into operations. Concerns about the future of work, including issues related to data privacy, human value, biases, and transparency, have accompanied the rise of enterprise AI. Nevertheless, there is also optimism regarding AI’s potential to enhance decision-making, stakeholder relationships, and innovation. Top management support plays a crucial role in facilitating AI adoption within organizations, with strong leadership seen as essential to overcoming adoption-related challenges. The technology-organizational-environment (TOE) framework provides a useful lens for understanding the adoption of AI within socioenvironmental and technological contexts. Despite significant progress in understanding AI adoption from an organizational perspective, the perspectives of employees remain relatively understudied. This research aims to address this gap by exploring how employees’ cognitive and affective attitudes toward AI influence their behavioral responses during the pre-adoption phase. By utilizing the cognitive appraisal theory, this study seeks to uncover the factors shaping employees’ attitudes toward AI and their intentions to use or leave organizations. Understanding these dynamics is essential for promoting a conducive environment for AI adoption and fostering creativity and innovation in the workplace. Additionally, this study utilized a Google Form questionnaire to collect data from employees.
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Publication Date
12/31/45412
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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