  As artificial intelligence transforms a wide range of sectors and drives
innovation, it also introduces complex challenges concerning ethics,
transparency, bias, and fairness. The imperative for integrating Responsible AI
(RAI) principles within governance frameworks is paramount to mitigate these
emerging risks. While there are many solutions for AI governance, significant
questions remain about their effectiveness in practice. Addressing this
knowledge gap, this paper aims to examine the existing literature on AI
Governance. The focus of this study is to analyse the literature to answer key
questions: WHO is accountable for AI systems' governance, WHAT elements are
being governed, WHEN governance occurs within the AI development life cycle,
and HOW it is executed through various mechanisms like frameworks, tools,
standards, policies, or models. Employing a systematic literature review
methodology, a rigorous search and selection process has been employed. This
effort resulted in the identification of 61 relevant articles on the subject of
AI Governance. Out of the 61 studies analysed, only 5 provided complete
responses to all questions. The findings from this review aid research in
formulating more holistic and comprehensive Responsible AI (RAI) governance
frameworks. This study highlights important role of AI governance on various
levels specially organisational in establishing effective and responsible AI
practices. The findings of this study provides a foundational basis for future
research and development of comprehensive governance models that align with RAI
principles.
