Embedding AI Governance in Organizations: A Multi-Level Approach to Responsible AI Use

This is the authors' abstract. We don't add key points for this paper.

Organizations now require stronger internal governance structures because artificial intelligence (AI) technologies continue to penetrate deeper into their operational processes. The GDPR and EU AI Act establish essential regulatory bases, yet organizations still face numerous practical challenges when implementing responsible AI practices. The European Commission continues to work on standardization initiatives to address this gap, but organizations must establish internal governance systems to convert external ethical standards into operational practices. This research examines organizational AI governance structures and implementation practices through twelve expert interviews representing technology, consulting and public administration sectors. This study demonstrates that organizations use a governance structure which includes strategic direction and operational execution and functional coordination and implementation through human resources and support functions. Furthermore, it also shows that internal governance operates dynamically based on specific roles and departmental collaboration and requires continuous adaptation and thus fills a knowledge gap between theoretical ethical standards and actual organizational implementation practices. Finally, this research provides operational recommendations for managers who want to establish AI governance systems in their organizations through cultural alignment and transparency and proactive change management.