Jun 2026· Economics Ecology Socium· Vol 10, pp. 81-93· 0 citations· 36 references
TL;DR
These insights demonstrate that successful public sector AI governance requires moving beyond mere regulatory compliance to embrace targeted capacity-building, institutional learning, and well-defined national implementation strategies, and introduce a holistic framework for the sustainable governance of AI systems.
Abstract
Background. To successfully modernise public governance for the digital era, the strategic adoption of artificial intelligence (AI) is an absolute necessity. The AI, however, cannot deliver sustainable value in a vacuum. Unlocking its true potential depends on institutional readiness, proactive regulatory frameworks, and robust governance capacity to mitigate both operational and societal risks.
Purpose. This study aims to examine how the evolving EU AI Act’s governance framework shapes the concept of Sustainable Digital Governance and to evaluate AI literacy and institutional readiness among Croatian civil servants as critical prerequisites for responsible AI deployment.
Findings. This empirical study utilises survey data collected in mid-2025 from Croatian civil servants to evaluate AI literacy, perceptions, and organisational readiness. While these preliminary findings are subject to certain methodological limitations, they reveal a severe implementation gap between regulatory mandates and institutional capacity. 73.6% of surveyed officials reported no prior exposure to AI-related training or professional discourse, and 80.2% could not identify high-risk AI systems within their operational environments. 62.6% noted a lack of organisational guidance on AI software utilities and their associated risks, leaving only 25.3% who felt capable of executing tasks in compliance with AI Act risk-mitigation standards.
Implications. These insights demonstrate that successful public sector AI governance requires moving beyond mere regulatory compliance to embrace targeted capacity-building, institutional learning, and well-defined national implementation strategies. Ultimately, this study synthesises theoretical perspectives with empirical data to introduce a holistic framework for the sustainable governance of AI systems. It concludes with actionable recommendations designed to guide policymakers and organisational leaders through the regulatory and operational complexities of an AI-driven landscape.
An academic adaptation of Patrick Rudolf Dannacher's presentation at the 10th Jakarta Geopolitical Forum 2026 is presented, examining Indonesia's strategic position in the evolving global AI landscape.
Patrick Rudolf Dannacher Dannacher· Proceeding Jakarta Geopoliti...· 1 citation
Artificial intelligence (AI) is revolutionizing higher education through personalized learning and data-driven administration. However, effective governance remains an essential issue for AI adoption, particularly in developing countries such as Morocco, where research is still limited. This study examines the role of governance structures, stakeholder engagement, and institutional preparedness in AI adoption within Moroccan universities through a systematic literature review of 37 peer-reviewed articles from Scopus (2020-2026), using PRISMA guidelines and thematic synthesis. Findings reveal a surge in AI studies since 2024, mostly conceptual and from Global North countries, highlighting multi-level, ethical, participatory, and anticipatory governance models. Stakeholder participation remains mostly top-down, with minimal faculty and student engagement, while readiness comprises infrastructure, literacy, leadership, and policy frameworks. Morocco has centralized control through Law 59.24 and Maroc AI 2030, but lacks context-specific studies. The study offers the Inclusive AI Governance-Readiness Framework, connecting institutional coordination, stakeholder engagement, readiness, and ethics for sustainable AI integration.
Doha Baladi, B. Guennoun· Journal of Interdisciplinary...· 0 citations
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.
Chijioke I. Okorie· Potchefstroom Electronic Law...· 0 citations
Artificial Intelligence (AI) is a transformative technology, that is reshaping the nature of governance systems, creating an unprecedented playing field for sustainable, efficient, and citizen-centric initiatives. It seems there are many challenges when it comes to the use of AI for governance purposes, with both theoretical and ethical gaps in the implementation process. This article discusses the function of AI in the field of sustainable governance and examines global publication trends, thematic interests, and collaborative patterns from 2000 to 2019. In this study, based on a sample of 1044 Scopus-indexed papers, a bibliometrics- and content analysis-based approach is used to identify the major themes, emerging topics, and geographic considerations of the merger of AI and sustainability. The Results indicate that while AI has been studied extensively in various domains (e.g. smart cities, e-governance, environmental management), ethical governance mechanisms, just policy implementation, and broader social implications of AI adoption have received insufficient attention. Filling these gaps, this study contributes to theory development in governance research and is relevant for policymakers to make the deployment of inclusive and ethical AI a reality. This analysis also underscores the importance of concerted interdisciplinary research efforts to strengthen the resilience, trust, and transparency of governance. One clear area in which the research described in this paper does not cover the broad impact of AI technology on sustainability is in developing countries
Empirical evidence is provided for the high relevance of procurement for public sector AI services via supplier-related governance perspectives and for the need to refine existing AI readiness and adoption models, particularly for regulated or defense-related procurement environments.
Max Ernst Hamscher, A. Glas, Michael Essig· International Journal of Pub...· 0 citations
