Sep 2026· Academic Journal of Research and Scientific Publishing· 0 citations
Abstract
This paper aims to develop an integrated framework for governing the adoption of artificial intelligence (AI) in government administration by linking AI adoption with governance, data privacy, transparency, accountability, workforce readiness, and regulatory controls spanning the system's lifecycle. The paper employs an integrative review of recent literature and a comparative analysis of policies and regulatory documents, focusing on Saudi Arabia as the primary context while drawing upon relevant experiences from the international models. The analysis reveals that successful AI adoption in government administration depends not only on technical and organizational readiness but also requires integrating data protection and privacy, algorithmic transparency, accountability, human oversight, and workforce capacity building into the adoption process itself. Furthermore, the paper highlights the importance of transitioning from general AI governance to operational protocols that define requirements for pre-adoption, design or procurement, testing, deployment, and monitoring and auditing. Accordingly, the paper proposes the "Integrated Framework for Responsible Government AI Adoption" (IF-RGA), which links use-case readiness, data privacy, transparency and accountability, workforce readiness, and risk-based governance across the lifecycle. The framework provides a conceptual foundation that can inform the development of government policies and future studies on AI adoption maturity, particularly within the Saudi and Gulf contexts.
The findings demonstrate that the adoption of responsible AI cannot be achieved through technological means alone but also requires a commitment to comprehensive governance mechanisms, and the sequential interaction and interdependence of governance factors reduce operational and societal risks, increase transparency a...
Ghazwan Hani Hussein, Faiza Mohamed, A. Abuzreda· Journal of Technology and Sy...· 0 citations
The STAGE framework is proposed as a practical approach to maintaining human judgment and organizational accountability when integrating AI into regulatory compliance and focuses on whether organizations can use AI to identify risks while keeping qualified people responsible for interpreting alerts, making decisions, d...
Monisade Oluwagbemigun· International journal of res...· 0 citations
Artificial Intelligence (AI) is increasingly embedded across public administration, business, education, communication, and other social and economic sectors. While this integration offers new opportunities for innovation and improved efficiency, it also raises concerns about privacy, transparency, accountability, fair...
Albert Andrew Kikuli· East African Journal of Law...· 0 citations
Background: The rapid adoption of artificial intelligence (AI) in human resource management has transformed recruitment, employee evaluation, workforce analytics, and decision-making. However, the growing use of AI also introduces ethical concerns, algorithmic bias, privacy risks, accountability challenges, and increas...
Jaganathan Balaji· International Journal of Inn...· 0 citations
The paper designs the Governance to Evidence Responsible AI Framework, which contains six governance control domains: mandate and ownership, data and fairness, model validation, decision orchestration, human accountability and continuous assurance.
Artificial intelligence (AI), and generative AI in particular, is rapidly reshaping how financial services firms operate, from investment research and portfolio analytics to marketing communications, financial promotions, compliance, and risk management. While the potential efficiency and scalability gains are signific...
Johanna Anders· Journal of financial complia...· 0 citations
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