Abstract The rapid adoption of artificial intelligence (AI) across sectors has intensified the need for governance mechanisms that ensure its ethical, transparent, and accountable use. While governments, industry bodies, and civil society organizations have introduced numerous principles-based and values-driven frameworks, translating these high-level guidelines into practical governance practices remain a persistent challenge. This principles-to-practice gap is particularly pronounced given the increasing complexity, opacity, and adaptive nature of contemporary AI systems. This paper adopts a normative and conceptual approach to examine how this gap can be addressed. We identify the main risks associated with AI systems throughout their lifecycle and review existing governance initiatives to critically analyze the potential of blockchain technology as an enabling governance infrastructure in AI systems providing greater transparency, auditability, and accountability in AI development and use. We propose a conceptual governance framework that provides initial guidance on the types of governance-relevant data that can be stored on a blockchain layer of AI systems throughout their lifecycle. The paper offers a structured conceptual foundation for embedding governance mechanisms into AI systems, highlighting key technical, organizational, and societal considerations and contributing to ongoing debates on operationalizing AI governance. The proposed framework informs future empirical and design-oriented research. The paper has significant implications for advancing AI governance considering the merging of two transformative technologies and promoting the ethical and responsible use of AI.
Wafaa A.H. Ahmed (Mon,) studied this question.