<![CDATA[Artificial intelligence systems are increasingly deployed in consequential domains, raising critical questions about governance, domain-specific applications, and emerging challenges. This paper examines the evolving landscape of responsible AI implementation across regulatory frameworks, high-stakes domains, and future research directions. It analyzes diverse regional governance approaches—from the EU's comprehensive risk-based regulation to the US's sectoral framework and East Asian models—alongside industry self-regulation mechanisms including standards, certification programs, and auditing methodologies. The research investigates domain-specific responsible AI practices in healthcare, criminal justice, financial services, and education, identifying tailored approaches to fairness, transparency, privacy, and stakeholder engagement. The paper further explores emerging challenges including foundation model governance, environmental sustainability, global equity, and AI systems reasoning about ethics. It concludes by mapping promising interdisciplinary research directions, addressing persistent knowledge gaps, and identifying essential methodological innovations and infrastructure needed to advance responsible AI practice. This comprehensive analysis offers researchers, practitioners, and policymakers practical frameworks for implementing responsible AI in an era of rapidly expanding capabilities.]]>
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