Artificial Intelligence (AI) has rapidly transformed business operations by enhancing decision-making, automation, customer engagement, and organizational efficiency. However, the widespread adoption of AI has simultaneously intensified concerns regarding data privacy, algorithmic bias, transparency, accountability, and ethical governance. These challenges have elevated the importance of Responsible Artificial Intelligence (Responsible AI) as a strategic priority for organizations seeking to balance technological innovation with ethical responsibility and regulatory compliance. This study presents a systematic literature review that synthesizes existing research on Responsible AI within business organizations. Relevant studies published between 2016 and 2026 were identified through leading academic databases using predefined inclusion and exclusion criteria. The selected literature was analyzed through a thematic approach to examine the current state of knowledge, emerging research trends, governance mechanisms, ethical principles, and implementation challenges associated with responsible AI adoption. The review identifies six major themes, namely AI adoption in business, ethical principles of AI, data privacy and regulatory compliance, organizational governance, algorithmic fairness and transparency, and implementation challenges. The findings indicate that although organizations increasingly recognize the strategic importance of responsible AI, significant gaps remain in governance maturity, organizational readiness, employee awareness, and practical implementation frameworks. Based on the synthesized literature, this study proposes an integrated conceptual framework highlighting the interrelationship between AI governance, ethical principles, data privacy, organizational accountability, and sustainable business outcomes. The review contributes to the existing literature by consolidating fragmented knowledge, identifying critical research gaps, outlining future research directions, and providing practical insights for researchers, business leaders, and policymakers seeking to promote trustworthy and responsible AI adoption.