The rapid diffusion of artificial intelligence (AI) across industries has intensified debates surrounding corporate social responsibility (CSR), sustainability, governance, and ethical accountability. While AI offers transformative potential for operational efficiency, innovation, and environmental optimization, it simultaneously introduces profound ethical, legal, and socio-political challenges. This study develops a comprehensive theoretical and empirical analysis of the intersection between AI governance and CSR, drawing exclusively on contemporary scholarship in business ethics, sustainability, information systems, and public policy. The research synthesizes insights from corporate sustainability frameworks, open innovation theory, AI ethics principles, auditing mechanisms, political economy perspectives, and sector-specific applications such as healthcare and financial services.

Using a qualitative meta-synthesis methodology grounded in systematic interpretive analysis, the study identifies key dimensions shaping responsible AI adoption in global enterprises: managerial attitudes toward standardization and social responsibility; open innovation as a pathway to shared value creation; political and economic tensions in AI-driven supply chains; ethical paradoxes in consumer markets; regulatory limitations in legal personhood; trust and accountability infrastructures; and the role of business intelligence in enabling transparent AI systems. The findings reveal that corporate AI governance remains fragmented, often driven by reputational risk mitigation rather than integrated sustainability strategies. Moreover, AI auditing practices face structural limitations that undermine meaningful accountability, while AI-driven “green” supply chain claims may obscure hidden environmental externalities.

The discussion advances a multidimensional governance model that integrates principle-based regulation, organizational culture, auditing reforms, stakeholder engagement, and business intelligence analytics. The study concludes that responsible AI must move beyond compliance-based ethics toward embedded sustainability-oriented governance structures that align technological innovation with societal expectations.

Artificial intelligence governance, corporate social responsibility, sustainable innovation, AI ethics, accountability, open innovation, corporate sustainability

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