Journal of Primeasia
Integrative Disciplinary Research | Online ISSN 3064-9870 | Print ISSN 3069-4353
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Volume 7 Number 1 2026
REVIEWS (Open Access)
Governing Artificial Intelligence for Sustainable Corporate Performance: A Systematic Review and Meta-Analytical Synthesis of Internal and External Governance Mechanisms
Tanveer Ahmed Siddquee 1*
Journal of Primeasia 7 (1) 1-8 https://doi.org/10.25163/primeasia.7110827
Submitted: 15 June 2026 Revised: 01 August 2026 Accepted: 11 August 2026 Published: 13 August 2026
Abstract
The rapid integration of artificial intelligence (AI) into corporate operations has fundamentally transformed governance practices, decision-making structures, and sustainability outcomes. While AI-enabled systems promise enhanced efficiency, transparency, and risk management, they also introduce new governance challenges related to accountability, ethical oversight, and institutional alignment. Despite a growing body of empirical research examining AI and corporate governance, existing evidence remains fragmented across disciplines, methodologies, and national contexts. This study addresses this gap by conducting a systematic review and meta-analytical synthesis of empirical research on the relationship between AI and digital systems and corporate governance outcomes, with particular attention to internal and external governance mechanisms. Drawing on Resource-Based View, Contingency Theory, Agency Theory, and Institutional Theory, the study integrates findings from quantitatively robust studies to estimate pooled effect sizes for key governance outcomes, including decision-making efficiency, financial transparency, risk management, executive control, stakeholder engagement, and corporate sustainability performance. The meta-analysis reveals that AI-enabled systems exert a statistically significant and positive influence on governance quality, with stronger effects observed when internal capabilities—such as high-quality information systems and managerial expertise—are aligned with supportive external institutional environments. However, the findings also highlight substantial heterogeneity across contexts, underscoring the importance of regulatory frameworks, ethical oversight, and organizational culture in shaping AI’s governance impact. By consolidating dispersed empirical evidence, this study advances a comprehensive understanding of how AI can be governed responsibly to enhance corporate performance and sustainability. The results offer important theoretical contributions and practical insights for policymakers, boards of directors, and corporate leaders seeking to harness AI while mitigating governance risks.Keywords: Artificial intelligence; corporate governance; sustainability performance; systematic review; meta-analysis; digital systems; ESG
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