Generative AI-Driven Collaborative Governance in Intelligent Societies: A Multistakeholder Framework for Trust, Accountability, and Inclusive Innovation

Abstract:

Generative AI (GenAI) has emerged as a transformative force in intelligent societies, yet its rapid proliferation poses unprecedented governance challenges—from algorithmic bias and misinformation to labor market disruptions. This study develops a multistakeholder collaborative governance framework integrating government regulators, technology developers, civil society, and end-users through a mixed-methods approach: a systematic literature review (n=214), 32 expert interviews, and three in-depth case studies (EU AI Act implementation, OpenAI’s Governance Board, and India’s GenAI for Public Good Initiative). The findings identify four core governance pillars—Proactive Regulation, Technological Safeguards, Stakeholder Co-Creation, and Adaptive Oversight—that address GenAI’s unique risks while unlocking its inclusive potential. The framework bridges gaps in existing research by moving beyond siloed governance models to emphasize dynamic, cross-sector collaboration. Practical implications for policymakers, developers, and civil society highlight the need for trust-centric governance that balances innovation with societal well-being. This research contributes to intelligent society discourse by providing a actionable roadmap for responsible GenAI adoption at scale.