Prioritizing AI Assurance and Civil Society Engagement Following India’s AI Impact Summit

2026-02-19 · Source: Partnership on AI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Public Policy & Governance, Regulatory & Compliance · Depth: Intermediate, medium

Summary

The AI Impact Summit in New Delhi, the first international AI summit hosted in the Global South, underscored two critical priorities for global AI governance: ensuring meaningful participation by civil society and strengthening the AI assurance ecosystem. While policy efforts like the US AI Action Plan and EU AI Continent Action Plan promote AI adoption, the Summit emphasized moving beyond high-level principles to measurable outcomes in both beneficial AI adoption and risk mitigation. The "Inclusion for Social Empowerment" Chakra highlighted the need for locally relevant and culturally respectful AI, requiring civil society engagement in governance. The "Safe and Trusted AI" Chakra focused on democratizing governance tools, but the article argues for broader ecosystem reform. The current AI assurance ecosystem is fragmented, lacking professionalization and market demand for independent assurance, with developing countries facing acute challenges due to diverse contexts and capacity constraints.

Key takeaway

For Directors of AI/ML evaluating governance strategies, you should prioritize integrating civil society input into your AI development and deployment frameworks. Your organization's long-term trust and ethical standing depend on moving beyond technical compliance to embrace broader social, institutional, and legal realities in AI assurance. Actively seek partnerships with civil society and academic experts to build a more robust and inclusive assurance ecosystem.

Key insights

Effective global AI governance requires civil society participation and a robust, inclusive AI assurance ecosystem.

Principles

• AI governance must reflect global needs.
• Assurance builds trust across the AI value chain.
• AI assurance needs iterative integration.

Method

Strengthening the AI assurance ecosystem involves investing at ecosystem and component levels, integrating assurance into the AI lifecycle, improving access for external assurers, and empowering AI safety institutes.

In practice

• Engage civil society in AI governance decisions.
• Develop flexible, locally grounded AI assurance strategies.
• Fund collaboration across industry, civil society, academia.

Topics

• AI Governance
• AI Assurance
• Civil Society Engagement
• Global South AI

Best for: Policy Maker, AI Ethicist, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Partnership on AI.