This paper aims to investigate how private corporations influence AI governance and explores mechanisms to rebalance corporate power with state sovereignty and public accountability. It assesses regulatory inconsistencies, enforcement gaps and policy tools for harmonizing AI governance across jurisdictions.
A comparative governance analysis is used to assess corporate-led and state-driven AI regulatory models. Case studies from China, the European Union and the USA illustrate tensions between corporate influence, public accountability and sovereignty. The analysis integrates legal frameworks, policy evaluation and theoretical perspectives to propose a multi-stakeholder governance framework combining corporate accountability, legal enforcement and transnational coordination.
Corporate-led AI governance often surpasses state oversight, resulting in accountability deficits and regulatory fragmentation. Transparency mandates, liability regimes and global enforcement coordination are identified as critical interventions. The study also highlights challenges posed by decentralized AI, autonomous systems and quantum computing.
States must strengthen enforceable AI regulations; corporations should implement robust transparency and compliance protocols; and global institutions must promote regulatory convergence. The study recommends expanding empirical policy research and case studies beyond dominant jurisdictions.
This paper reframes AI governance debates by moving beyond voluntary ethics toward enforceable regulatory architectures. It introduces novel strategies for managing emerging AI risks, preventing regulatory arbitrage and ensuring accountable cross-border compliance.
