Transforming Chartered Governance Through AI and Big Data

This study investigates the transformative integration of Artificial Intelligence (AI) and Big Data into chartered governance, bridging the gap between traditional governance practices and the potential of these advanced technologies. Employing a qualitative methodology with semistructured interviews of 20 governance professionals, the research explores benefits, challenges and ethical considerations. The findings reveal significant enhancements in efficiency, accuracy and decision-making, alongside barriers such as data privacy concerns, algorithmic complexity and skill gaps. This study extends theoretical frameworks including the Technology Acceptance Model (TAM), Resource-Based View (RBV) and Institutional Theory, providing empirical insights into the interplay of technology, organisational strategies and regulatory demands. Practical recommendations include phased implementation, staff training, establishing ethics committees and fostering interdisciplinary collaboration. This study provides a foundation for future research to further explore the evolving integration of AI and Big Data in governance, addressing emerging trends and fostering innovation.

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Publication Details

Published
2024-11-28
DOI
https://doi.org/10.1109/zcict63770.2024.10958226
Citations
1
Primary Topic
Corporate Insolvency and Governance
Type
article
Field-Weighted Citation Impact
0.95
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article

Transforming Chartered Governance Through AI and Big Data

Colletor Tendeukai Chipfumbu, Theo Tsokota, Martin Muduva
1 citations
Corporate Insolvency and Governance
0.95
article

Transforming Chartered Governance Through AI and Big Data

Colletor Tendeukai Chipfumbu, Theo Tsokota, Martin Muduva
article en
1 citations

Abstract

This study investigates the transformative integration of Artificial Intelligence (AI) and Big Data into chartered governance, bridging the gap between traditional governance practices and the potential of these advanced technologies. Employing a qualitative methodology with semistructured interviews of 20 governance professionals, the research explores benefits, challenges and ethical considerations. The findings reveal significant enhancements in efficiency, accuracy and decision-making, alongside barriers such as data privacy concerns, algorithmic complexity and skill gaps. This study extends theoretical frameworks including the Technology Acceptance Model (TAM), Resource-Based View (RBV) and Institutional Theory, providing empirical insights into the interplay of technology, organisational strategies and regulatory demands. Practical recommendations include phased implementation, staff training, establishing ethics committees and fostering interdisciplinary collaboration. This study provides a foundation for future research to further explore the evolving integration of AI and Big Data in governance, addressing emerging trends and fostering innovation.

Midlands State University (ZW)
Openalex Percentile: Top 16%
Corporate Insolvency and Governance
0.95
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