AI as a tool to enhance corporate governance compliance in the public sector in Kuwait
Abdullah E. Alajmi
Abstract
Purpose This study aims to explore the transformative impact of artificial intelligence (AI) on corporate governance within Kuwait’s public sector, focusing on how AI enhances transparency, accountability and decision-making. Design/methodology/approach The research employs a mixed-methods approach, analyzing the integration of AI in governance frameworks through both quantitative data and qualitative insights from key stakeholders. It examines how AI technologies streamline compliance, mitigate risks and improve operational efficiency in public institutions. Findings The study reveals that AI, when strategically implemented, significantly enhances governance structures by improving transparency and institutional effectiveness. However, challenges related to ethical considerations and the need for a regulatory framework tailored to Kuwait’s unique political and cultural context must be addressed for successful adoption. Research limitations/implications The study is limited by its focus on Kuwait’s public sector, which may not fully reflect AI adoption challenges and opportunities in other regions. Future research should consider broader comparative studies to examine AI’s governance impact across different socio-political environments. Practical implications The findings offer actionable insights for policymakers in Kuwait, providing a roadmap for integrating AI in governance to enhance public trust and institutional performance. Originality/value This paper contributes to the growing discourse on digital governance by presenting Kuwait as a case study for how AI can be utilized to modernize public sector governance. It offers new perspectives on overcoming the challenges of AI adoption in government institutions.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.