Artificial intelligence for identifying predatory litigation in Brazil: A literature mapping and technical review

This article investigates the application of artificial intelligence (AI) to address repetitive and predatory litigation in Brazilian courts through a literature mapping and technical review. In recent years, the Brazilian judiciary has experienced a surge in predatory litigation, leading to increased case backlogs and inefficiencies. Leveraging AI tools for litigation identification and classification presents a promising avenue to mitigate these challenges. This study systematically maps existing scientific literature and reviews AI-driven tools deployed within the Brazilian judicial system to combat repetitive claims, with particular attention to initiatives such as the Bastião Project, Genesis, and Sherlock systems. By examining the technological approaches, challenges, and reported outcomes of AI in managing predatory litigation, this paper highlights AI’s potential to support judicial efficiency and integrity. The findings suggest the need for continuous refinement of AI models to address ethical considerations, data transparency, and adaptation to evolving judicial demands.