The rise of Artificial Intelligence (AI) in the collection and processing of personal data poses significant legal challenges, particularly regarding compliance with the General Data Protection Law (LGPD). Decision-making automation, enabled by machine learning and deep learning, increases the need for traceability and transparency in the processing of personal information. However, algorithmic opacity and the biases embedded in predictive models hinder corporate accountability for potential privacy and data protection violations. Brazilian regulation still struggles to harmonize technological innovation with existing legal frameworks, as evidenced by recent issues related to automated decisions and leaks of sensitive data. The role of the National Data Protection Authority (ANPD) has been crucial in setting regulatory guidelines and best practices for AI governance, demanding greater corporate accountability in complying with the LGPD. Given the complexity of this issue, this study analyzes the civil liability of organizations for the misuse of AI in the processing of personal data, considering legal implications, regulatory challenges, and impacts on data subjects’ rights. The research explores the need for specific regulation of high-risk AI, the strengthening of compliance measures, and the adoption of algorithmic audits as mechanisms to mitigate risks. It concludes that the balance between innovation and data protection requires policies of transparency, algorithmic explainability, and more robust regulatory oversight to ensure compliance with the principles of the LGPD.
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