On August 29, CEBRI hosted an international seminar, in partnership with Brazilian and international institutions, to discuss pathways for governing artificial intelligence in Brazil.

The event brought together representatives from the public sector, academia, civil society, and international organizations to explore how the country can build a transparent, inclusive, and forward-looking institutional framework.

Drawing on international case studies and local expertise, the seminar examined strategies for interinstitutional coordination, transparency mechanisms, risk mitigation, and regulatory approaches that strike a balance between innovation, competitiveness, and responsibility.

Organized by the Brazilian Center for International Relations (CEBRI), in partnership with the Brazilian Network Information Center (NIC.br), the International Research Center on Artificial Intelligence under the auspices of UNESCO (IRCAI), the Brazilian Observatory of Artificial Intelligence (OBIA), and the Artificial Intelligence and Machine Learning Center (CIAAM) at Inova USP, the seminar featured three panels:

Institutional Coordination for AI Governance in Brazil

This panel emphasized the need for an institutional arrangement that ensures clarity and consistency in AI governance. It also highlighted the importance of framing AI not only as a regulatory challenge but as an opportunity for tangible gains in sectors such as healthcare, agriculture, and finance. In summary, the panel advocated for a cooperative governance model built on regulatory clarity, institutional coordination, practical support tools, and aligned industrial policies.

Transparency, Accountability, and Risk Mitigation in AI Systems

The second panel addressed both normative and practical foundations of AI governance, focusing on transparency, accountability, and risk mitigation. Transparency was presented as a central element, requiring contextual implementation across scientific, regulatory, and public domains. The discussion underscored the need for standardization, interoperability, and shared methodologies to ensure transparency leads to accountability. It also emphasized the importance of distributing responsibilities throughout the AI value chain, including logging, auditing, and impact assessments. The panel warned of the risks posed by an “informal AI economy” and recommended the adoption of internal policies for the responsible use of AI in both public and private organizations.

Lessons from International Models: Sandboxes, Agencies, and Cross-Border Governance

This panel presented international experiences in AI governance, emphasizing the importance of adapting global best practices to the Brazilian context. Principles such as inclusion, transparency, human rights, and accountability are widely recognized; the challenge lies in translating them into practical institutional actions. The panel emphasized the importance of independent and capable bodies, as well as the adoption of standardized methodologies for auditing and impact assessment. The discussion converged on the need for a continuous, dynamic, and multisectoral AI governance model in Brazil, one that is aligned with international principles and industrial policies.

The seminar’s discussions converged on the view that AI governance must be continuous, dynamic, and multisectoral, guided by principles of transparency, accountability, inclusion, and human rights. Building this model requires institutional coordination, strengthened technical capacity, the use of adaptive tools such as sandboxes and audits, and integration between regulation and industrial policy. If Brazil succeeds in articulating these elements, it has the potential to position itself as a global leader in the field of artificial intelligence.