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                <text>Faculty Publications</text>
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              <text>Hiremath, Sony; P, Ramesh; Konek, Shailaja S.; Bhavikatti, Veena Ishwarappa; vemula, Rajesh; B, Omnamasivaya</text>
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              <text>Artificial intelligence (AI) governance in organizational decision-making: balancing autonomy, accountability and transparency</text>
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              <text>01-01-2025</text>
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              <text>Journal of Entrepreneurship and Public Policy;pp.1-24</text>
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              <text>&lt;a href="https://doi.org/10.1108/JEPP-04-2025-0112" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1108/JEPP-04-2025-0112&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105024694657?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105024694657?origin=resultslist&lt;/a&gt;</text>
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              <text>Hiremath S., Visvesvaraya Technological University, Belagavi, India; P R., Brainware University, Kolkata, India; Konek S.S., Central University of Karnataka, Kalaburagi, India; Bhavikatti V.I., Dayananda Sagar Business School, Bangalore, India; vemula R., Christ Deemed to be University, Bangalore, India; B O., Gonna Institute of Information Technology and Sciences, Visakhapatnam, India</text>
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              <text>Purpose  This study aims to investigate the ethical and practical implications of delegating decision-making to AI systems, focusing on the necessity for a robust governance framework. Specifically, it examines how autonomy, transparency and accountability within AI governance influence organizational decision-making. Design/methodology/approach  Employing a quantitative survey methodology, this study gathered data from 452 business owners and managers in Indian IT companies. The questionnaire was disseminated using online platforms and departmental communication channels. Structural equation modelling (SEM) was utilized for data analysis, allowing for the examination of relationships among autonomy, transparency, accountability and decision-making. Findings  The findings indicate that autonomy, transparency and accountability significantly impact organizational decision-making processes. Specifically, autonomy and accountability were found to directly influence decision-making, while transparency also played a crucial role. Additionally, social innovation was identified as a significant moderating factor, enhancing the relationship between AI governance and decision-making outcomes. Originality/value  This research contributes to the existing literature on AI governance by elucidating the critical role of ethical frameworks in organizational decision-making. By incorporating social innovation as a moderating variable, the study offers novel insights into how AI governance can be optimized to enhance decision-making processes. The application of SEM provides a rigorous analytical approach, facilitating a deeper understanding of the interplay between governance dimensions and decision-making outcomes. The findings have practical implications for organizations seeking to implement effective AI governance strategies in their operations.  2025 Emerald Publishing Limited</text>
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              <text>Artificial intelligence; Business owners and managers; Decision-making; Structural equation modelling</text>
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              <text>Emerald Publishing</text>
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              <text>ISSN: 20452101;</text>
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              <text>Restricted Access; Hardcopy may be available in the library</text>
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