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A survey of 140 organizations with active ISO 27001 certification across Argentina, Brazil, Colombia, Mexico, and Peru found that 73% have at least one generative AI tool in operational use without formal security function approval. The departments with the highest unauthorized adoption are Marketing (89%), Human Resources (71%), and Finance (54%). The most common tools are ChatGPT (direct use without corporate API), unlicensed Copilot, and language model automations embedded in spreadsheets. 61% of ISO 27001:2022 Annex A controls related to asset management and access control proved insufficient to detect these tools because they do not recognize AI assets as a category. Four primary data leakage vectors were identified: prompts containing confidential client data (42%), uploading internal documents to public AI platforms (38%), using AI to generate code with embedded sensitive data (12%), and automations sending data to external APIs without logging (8%). The remediation model developed classifies Shadow AI into three risk tiers and proposes controls compatible with ISO 27001 and ISO 42001 without restricting productivity.
Central questions answered with verifiable data from the study.
73% of surveyed organizations have unauthorized use; in Marketing it reaches 89%.
Four primary vectors: prompts with client data (42%), internal document uploads (38%), code with sensitive data (12%), unlogged external APIs (8%).
61% of asset management and access controls do not recognize AI assets as a category, making them ineffective for Shadow AI detection.
Steps completed, sources consulted, and evidence collected during the study.
Normative and theoretical framework: ISO/IEC 27001:2022 (Annex A — access control, asset management, and communications security); ISO/IEC 42001:2023 (AI system inventory and governance); NIST AI RMF 1.0 (risk profile and GOVERN function); EU AI Act (2024/1689, Articles 4 and 6).
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