Artificial Intelligence Governance and Banking Regulatory Compliance: A Multiple-Case Study of Commercial Banks in Uganda

The Use of Artificial Intelligence in Enhancing Accountability and Transparency in South African Municipalities: Prospects, Barriers and Strategic Pathways for Local Government

This study examined how artificial intelligence (AI) can enhance accountability and transparency in South African municipalities. The study responded to persistent municipal governance challenges, including weak financial oversight, fragmented data systems, service delivery inefficiencies and declining public trust. A systematic review design was adopted to synthesise global, African and South African evidence on AI adoption in public administration and municipal governance. The review was guided by PRISMA principles and included 43 eligible studies selected from academic, policy and institutional sources. The Technology Acceptance Model and Institutional Theory were used to interpret both user-level and institutional factors influencing AI adoption, including perceived usefulness, perceived ease of use, staff readiness, organisational resistance, regulatory pressure and governance norms. The findings show that AI can support municipal accountability through fraud detection, procurement monitoring, audit support and anomaly identification. AI can also improve transparency through citizen-service chatbots, complaint-routing systems, open data tools and integrated information platforms. However, the review found that AI adoption in South African municipalities is constrained by poor digital infrastructure, weak data interoperability, limited technical skills, financial pressure, organisational resistance and unclear ethical governance arrangements. The study concludes that AI should be treated as a governance support tool rather than a complete solution to municipal failure. Its value depends on phased implementation, data modernisation, capacity building, legal safeguards, human oversight and inclusive citizen engagement. Future research should examine municipal-level AI implementation, public trust, algorithmic accountability and the effects of AI on equitable service delivery.

Rethinking the Governance of Artificial Intelligence Oversight in Indonesia from a Global Perspective

The rapid development of Artificial Intelligence (AI) has significantly transformed public governance, public services, and the digital ecosystem. However, such advancement has not been accompanied by the establishment of a comprehensive administrative legal framework in Indonesia. AI-related regulations remain fragmented across sectoral legal regimes, resulting in regulatory inconsistency, unclear supervisory authority, weak auditing mechanisms, and limited administrative accountability in AI deployment. This research aims to analyze the weaknesses of AI governance in Indonesia and reconstruct an administrative supervision model of AI from the perspective of Administrative Law, considering global regulatory practices. This study employs normative legal research using statutory, conceptual, and comparative approaches. The findings indicate that Indonesia has not yet established an integrated administrative governance framework for AI, particularly regarding regulatory authority, administrative discretion, algorithmic audits, certification, compliance oversight, and accountability of administrative bodies or public officials. Drawing from the European Union Artificial Intelligence Act, OECD AI Principles, and UNESCO Recommendation on the Ethics of Artificial Intelligence, this study proposes a reconstructed administrative governance model based on risk-based supervision, strengthened regulatory authority, compliance auditing, certification mechanisms, and institutional accountability. This research emphasizes that AI governance should be positioned as part of digital administrative governance and developed as a domain of Administrative Law to ensure legality, public interest protection, and legal certainty in the digital transformation era.

Governing artificial intelligence in the financial sector: regulatory challenges and policy implications in Saudi Arabia

From model assurance to pipeline accountability: vendor-mediated generative AI governance in regulated financial services in Singapore and Vietnam

This study aims to examine how digital policy and regulatory governance should respond to vendor-mediated generative artificial intelligence (AI) in regulated financial services. It argues that the central problem concerns not only model assurance but also the evidentiary pipeline through which customer data, vendor processing, generated outputs and human review become auditable. The article uses a conceptual and design-orientated documentary comparison of Singapore and Vietnam. It analyses AI governance, data protection, financial supervision and third-party risk instruments through four functional axes, derives operational indicators from the documentary corpus and examines their internal coherence through a structured illustrative case in financial services. Singapore’s interoperability-orientated model and Vietnam’s dossier-based model of legal visibility provide different regulatory entry points. Both remain incomplete unless institutions preserve workflow-level evidence across procurement, configuration, deployment, output verification and supervisory review. The framework links risk triggers to pipeline maps, vendor due diligence, transfer records, output-verification protocols and audit trails. The article develops a conceptually grounded pipeline accountability framework that connects vendor obligations, data movement, generated outputs and human verification. It is operationally specified but remains a design proposition requiring empirical testing and refinement.

Developing an Algorithmic Accountability and Data Sovereignty Framework for the governance of Artificial Intelligence platforms in United States education

This study showed how current policy architectures may permit the commercial use of student data and suggests immediate policy changes that would guarantee control of student data, ensure algorithmic accountability, and also prioritize the benefits of students over data monetization.

Towards a Transdisciplinary Governance of Artificial Intelligence in Africa

The governance of artificial intelligence (AI) in Africa faces competing pressures from demands for regulatory intervention alongside concerns about institutional capacity, innovation costs, and economic vulnerability. Debates surrounding algorithmic discrimination, biometric surveillance, and extractive data practices by global platforms have sharpened questions about the appropriate roles of states, markets, and civil society in governing AI systems. Yet existing governance scholarship tends to address these questions through either ethical principles or state-centric regulatory frameworks, leaving a significant analytical gap where law and technical design intersect. This article introduces legal-technical governance as an analytical framework for examining Africa’s emerging AI regulatory landscape. Distinguishing governance from regulation, the article argues that AI governance in Africa is already distributed across data protection statutes, fintech guidelines, cybersecurity frameworks, and content moderation policies imposed by global platforms, making a broader, systems-level analytical tool both necessary and timely. Legal-technical governance foregrounds the co-constitutive relationship between legal norms and technical operations, including data labelling, model training, and algorithmic auditing. It accounts for the various actors shaping AI outcomes, from multinational technology firms to standards bodies and affected communities. To examine the gaps where legal frameworks and technical systems diverge, the article draws on Dooyeweerd's modal aspects as a philosophical lens. Applied to African AI governance domains, this framework reveals how institutional fragmentation, infrastructural dependency, and global platform dominance undermine state-centred regulatory models. The article concludes by advancing legal-technical governance as a productive framework for scholarship and policymaking at the intersection of law, technology, and development in Africa.