Techno-judges on the spot: explorations of the impact of AI advancements in Brazil’s Justice System

This paper aims to analyse the effects of the implementation of AI decision-making tools in Brazil’s Justice System, focusing on judge’s work in two main courts in São Paulo, the State Court of São Paulo (TJSP) and the Federal Court of the Third Region (TRF3R). Considering the overall rise in AI adoption in public services, regardless of the area, stands the fact that there’s an enormous heterogeneity in all categories of AI use and application, as well as heterogeneities in the implementation process, the choice and development of such algorithmic models (Ribeiro & Segatto, 2025). These models and tools are usually developed and driven by the bureaucracy’s limited capabilities or through contracts of licenses, LLMs and other cloud-based services provided by Big Tech companies. AI tools may strengthen administrative capabilities and promote social inclusion in public policies (Andersson et al., 2022; Kerssens & Van Dijck, 2021), but there’s usually ethical and structural challenges, as well as multiple risks, such as algorithmic biases being made and reproduced through data and the probability of bureaucrats’ discernment being drastically reduced, which could entail in amplifying inequalities and compromising general public’s access to public services (Boer & Raaphorst, 2023; Bovens & Zouridis, 2002; Selten et al., 2023). Regarding Justice Systems, judges tend to use AI tools to accelerate the decision-making process, with the goal of reaching higher productivity metrics (CNJ, 2025; Kolkman et al., 2024), especially in Brazil’s case where the whole Justice System is over-loaded in number of pending cases, accounting a backlog of over 80 million. Thus, AI appears to these institutions and courts as a miraculous tool that will fix most, if not all, of their problems regarding speed, efficiency and productivity in the decision-making process. However, most of the literature regarding this theme focuses on the Global North. As such, the analysis of Brazil’s case fills an important gap in this discussion, by taking a look at different organizational contexts, which show a broader picture of public institutions’ capabilities and fragilities, especially regarding Justice Systems, since these differences play a main role in affecting the bureaucracies’ work (Nieto-Morales et al., 2024). In addition to this, this paper tackles another fundamental gap in the literature, of which there’s very few works taking a qualitative approach in social sciences to evaluating the impacts and perceptions of the users of these tools, specifically works that delve in bureaucrats, public servants and judges’ day to day work (Selten et al., 2023; Kapoor et al., 2024). We aim to contribute to this debate by evaluating the degree and the type of transformations perceived in judges’ position and function, as well as in jurisdictional work. We choose a period of five years, from 2020 to 2025, which proves to be a very important and transitional period for Brazilian Courts’ digital transformation. Thus, firstly we have drawn out some questions regarding the adoption of AI in public services, the digital transformation of Justice Systems and also questions on human-machine interaction. We also contextualize the current scenario of Brazilian Courts’ technological developments, by means of official documents published by the National Council of Justice (CNJ, 2025). As for our methodology, we relied on documents analysis (Cellard, 2012) and also in-depth interviews (Barbot, 2015), from which we gathered data on perceptions, practices and overall changes felt and reported by judges. The thematic analysis of those interviews revealed evidence that AI tools have been frequently used by the judiciary on a day to day basis, including informal uses of Chatbots and Gen AI services, mainly to support decision-making. Results also point to a high probability of over-reliance on these tools’ results by these judges, who expressed concerns regarding faults in AI but declared that they didn’t have enough training to comprehend or deal with such tools and their errors. As a byproduct of this paper, we find that a fairly clear scenario can be described: the AI implementation race by public services in Brazil has been excessively rushed and lacks critical thinking regarding when, why and how to adopt these tools. As such, we believe that these results may impact the development of better governance models for public sectors taken by digitalization and modernization processes (Mergel et al., 2023).