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The exponential development of Artificial Intelligence in the corporate functions has changed radically the way decisions are taken, the way risks are managed and how audits and performance is monitored. Existing studies mostly look at the relation between corporate governance and financial performance separately or deal with adopting AI without considering the dynamics of the governing. Moreover, the lack of standardised frameworks for AI disclosure particularly in emerging markets like India, means there are transparency gaps, accountability problems and also potential governance risks. This study attempts to create a conceptual framework is to integrate disclosing AI, Corporate Governance Mechanisms and Financial Performance using the theories of Agency Theory and Collective Action Theory. We show that the information asymmetry between managers and shareholders can be reduced by AI disclosure and this has implications on the oversight by the board, and builds trust between stakeholders. At the same time, collective board involvement in AI oversight helps to add to the credibility and effectiveness of disclosure practices. The analysis hence further identifies key characteristics of the boards include optimal size of the board, gender diversity, separation of the CEO and Chair roles and structure of board meeting as moderating factors in the governance performance nexus. While financial transparency enabled by AI makes audits better, operations more efficient and risks more detectable, challenges such as voluntary reporting practices, algorithmic bias and regulatory uncertainty increase the demand for adaptive governance models and standardized disclosure indices. The study contributes to the study of governance and technology as it proposes an integrated and theoretical framework of disclosing about AI as a strategic tool for high and sustainable financial performance and long-term competitive advantage.
Published in: International Journal of Global Research Innovations & Technology (IJGRIT).
Volume 04, Issue 01, pp. 165-170