Regulation of Artificial Intelligence: Between the Switch and Innovation — Is Brazil Prepared?
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Abstract
Objective: to examine whether Brazil’s proposed AI regulation promotes innovation and competitiveness in comparison with global regulatory models. Methods: qualitative, exploratory study using comparative document analysis of AI regulations in eight jurisdictions (USA, EU, UK, China, Brazil, India, Mexico, and Chile). The analysis applies Lessig’s regulatory vectors — law, architecture, market, and norms — alongside institutional theory. Results: findings show that regulatory effectiveness depends on institutional capacity, implementation mechanisms, and policy alignment. Conclusions: adaptive and sectoral models (e.g., UK, USA, Chile) better support innovation than prescriptive or fragmented frameworks. Brazil’s EU-inspired Bill 2338/2023 faces enforcement gaps, legislative overlaps, and uneven sandbox deployment, raising barriers for startups. Brazil’s attempt to replicate EU rules without corresponding capacity may hinder AI development. A hybrid, phased strategy combining legal convergence with institutional adaptation could enhance innovation and regulatory credibility in emerging markets.
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