Objective: To investigate Brazil's renewable energy policies and infrastructure for attracting green artificial intelligence (AI) technology investments, comparing its competitive position with other emerging markets. Theoretical Framework: This research is based on green technology investment theory, renewable energy policies, and digital infrastructure models. Sustainable development and technology adoption frameworks explain the relationship between energy policies and AI investments. Method: Systematic review of 23 studies from Semantic Scholar and academic sources. Data collection through structured searches, content analysis, and comparison of policy frameworks across emerging markets. Results and Discussion: Brazil offers a promising but less developed environment for green AI investments compared to leading emerging markets. The 90% renewable electricity matrix and BNDES financing of US78. 8 billion (2009-2018) demonstrate a commitment to renewable energy. However, regulatory unpredictability, integration challenges, and underdeveloped green bond markets limit competitiveness. Research Implications: Provides insights on how Brazil can improve its position in global green AI investments. Implications include recommendations for regulatory stability, grid modernization, and financial market development. Originality/Value: First comprehensive comparison of Brazilian renewable energy infrastructure for green AI investments. Its relevance lies in guiding policy and investment in the emerging green technology sector.
Julio Cesar de Aguiar (Fri,) studied this question.