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Inclusion in Translation explores how diversity and inclusion (D&I) efforts succeed or fail across multinational enterprises operating in different cultural, regulatory, and institutional contexts. Drawing on a 15-country dataset and grounded in Institutional Theory and Social Identity Theory, this book uncovers the hidden forces-governance structures, cultural norms, and policy frameworks-that shape D&I outcomes globally. Through advanced machine learning analysis, it reveals the non-linear patterns that explain why inclusion efforts thrive in some regions but falter in others. The book offers actionable insights for business leaders, policymakers, and scholars aiming to bridge the gap between global D&I ideals and local realities, while also integrating Environmental, Social, and Governance (ESG) principles into organizational strategies. This work provides a fresh, data-driven framework for understanding how inclusion can be both transformative and challenging within complex multinational settings.