The Role of Artificial Intelligence in Digital Sustainability and Governance Systems

• Дата: 2026
• Автори: Keser, Ivana, Mudrić, Mihael Mišo
• Формат: Стаття
• Мова: Англійська
• Опубліковано: Dr. Viktor Koval 2026
• Теми: Artificial Intelligence; AI Governance; AI Literacy; Digital Governance; Sustainability.
• Онлайн доступ: https://ees-journal.com/index.php/journal/article/view/345
• Назва журналу: Economics Ecology Socium

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.