Post-Event Outcomes Brief

The Next GenAI Forum: Preparing for Tomorrow’s AI Governance Today convened youth leaders, policymakers, researchers, and civil society actors on January 30, 2026. The aim was to examine how artificial intelligence is reshaping safety, labor, and opportunity with a deliberate focus on elevating Global Majority and youth perspectives in governance conversations. The event was hosted through participation hubs in Accra, Ankara, Astana, Montreal, and online across our international network. The hybrid format allowed cross-regional dialogue grounded in local realities, with ~230 attendees joining from 15+ countries. The forum centered on safe & trusted AI, inclusion and social empowerment, and youth futures in an AI-driven economy, using panels and a closing workshop to surface agency gaps and pathways for open engagement. This post-event brief synthesizes key youth-driven insights and recommendations intended to inform the India AI Impact Summit (2026) and strengthen ongoing policy contributions on the global stage.

1) Fortify Local AI Governance Capacity and Public-Interest Infrastructure

AI systems are only as safe and fair as the communities they serve, yet their rapid scaling is outpacing local institutions’ capacity to respond, widening the gap between deployment and effective governance. Without sustained investment, AI frameworks risk becoming symbolic, i.e., adopted in principle but unenforceable in practice, which highlights the need for local technical expertise, public-interest infrastructure, and tools to interpret and apply governance in context. Key barriers include limited readiness to assess AI in public services, difficulty in adapting global frameworks to local contexts, and the underrepresentation of youth in decision-making spaces.

Strengthening local capacity requires:

• Invest in local technical expertise, open data access, and audit mechanisms to ensure accountable AI deployment.
• Embed youth voices and cross-sector partnerships in governance to align with community needs.
• Build AI literacy and workforce foresight to prepare communities for labour market shifts and emerging opportunities.

2) Implement Risk Scanning and Response Through Capacity Building

Warning signs are often visible first to researchers, students, and practitioners close to deployment. Yet these signals rarely travel into decision pipelines and, without institutional homes, dissipate.

To operationalize this link, participants, we should:

• Establish standing horizon-scanning units within ministries to produce recurring assessments, maintain watchlists of emerging systems, and initiate regulatory reconsideration when predefined indicators are met.
• Enable structured cross-border exchange via shared reporting channels and regional coordination that can surface patterns before they escalate.
• Establish clear requirements for independent impact assessments before deploying AI systems and throughout the AI lifecycle, in both the private and public sectors.

3) Build Agile Regulatory Approaches to Reinforce Societal Resilience in the Face of AI Risks

If a system can change every month but a rule changes every five years, real authority migrates away from regulators. Moreover, the long-term effects of AI on society (such as its impact on democratic institutions) remain to be seen and fully understood. Without regulatory agility and societal adaptation, governance frameworks risk becoming symbolic and disconnected from how AI actually affects people on the ground. Even where capability appears limited, scale alone can amplify harm.

To reinforce societal resilience, we should:

• Design flexibility into legal instruments, such as sunset clauses and automated compliance, that can prevent rules from lagging behind capability shifts.
• Mandate AI systems used in public or high-risk private sectors provide clear documentation and meaningful contestability mechanisms, including performance limitations.
• Install safeguards in the digital information environment, such as watermarking and provenance measures, to protect the information commons.

AI’s trajectory remains uncertain. Technical progress, labor impacts, and governance needs may evolve in ways that are difficult to anticipate from today’s vantage point. However, when prediction is limited, adaptability becomes the core asset, and broadening who contributes to governance strengthens the system’s ability to respond. The next phase of global AI governance must be shaped in coordination with people entering the field today.

Organizing Committee

Heramb Podar (Lead Writer), Meriem Mehri (Lead Writer), Adrian Klaits, Joseph Awuah