A GPT-Based Assessment of Alignment Between Privacy Legal Frameworks & ISO/IEC 27701:2025: A Latin American Case Study

The 2025 update of the International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 27701 standard offers a major advantage by enabling organizations to implement a Privacy Information Management System (PIMS) autonomously while maintaining alignment with the General Data Protection Regulation (GDPR). However, it remains unclear to what extent privacy legal frameworks in developing jurisdictions, particularly in Latin American countries, align with this new standard. At the same time, the traditional method for assessing the alignment between privacy legal frameworks and ISO/IEC 27701 continues to rely on manual mapping between the standard’s subclauses and privacy regulatory articles, a process that is time-consuming, costly, and error-prone. More critically, no method exists to quantitatively assess the reliability of such mappings, leaving alignment assessments largely subjective. To address these limitations, this paper proposes a novel method based on an OpenAI Generative Pre-trained Transformer (GPT) combined with a Chain-of-Thought (CoT) reasoning strategy to quantitatively assess the alignment between privacy legal frameworks and ISO/IEC 27701:2025. By leveraging GPT’s logarithmic probabilities (logprobs) and the standard’s subclause definitions as classification categories, the method enables confidence-based evaluation of legal–standard alignment. The proposed method is then applied to analyze the privacy legal frameworks of Paraguay, Chile, Ecuador, México, Colombia, and Perú, examining how effectively they promote the standard’s guidelines. A suitable confidence threshold is then selected by assessing the GDPR and comparing the results with the reference mappings reported in Annex D of the standard. Finally, the method identifies the number of compliant subclauses per clause, the regulatory articles influencing the resulting logprobs, and the underlying privacy gaps for reduced alignment across the analyzed privacy legal frameworks. Overall, our results indicate that while Latin American privacy legal frameworks mandate protective measures by promoting a suitable operation and continuous improvement of a PIMS, they do not explicitly demand adequate risk management and sufficient preventive safeguards for citizens’ Personally Identifiable Information (PII) in dynamic contexts.