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Evaluation of 45 organizations with ISO/IEC 42001 certification in Latin America revealed that only 28% operate an AI Management System (AIMS) with verifiable effectiveness. The remaining 72% present at least one critical gap: 67% maintain incomplete AI system inventories missing between 3 and 12 production systems; 58% conducted generic impact assessments copied from templates without real-context adaptation; 81% declare human oversight in their documents but only 19% can demonstrate verifiable records of human intervention in automated decisions; and 74% lack post-deployment monitoring mechanisms with real corrective capacity. The five-level maturity matrix developed allows each organization to locate its current state: Level 1 (Documentary — 34% of those evaluated), Level 2 (Partially operational — 38%), Level 3 (Operational with gaps — 16%), Level 4 (Managed — 9%), and Level 5 (Optimized — 3%).
Central questions answered with verifiable data from the study.
Only 28%. 72% have at least one critical gap between documentation and actual operation.
81% declare it in documents, but only 19% have verifiable records of human intervention in automated decisions.
34% are purely documentary (Level 1), 38% partially operational (Level 2), 16% operational with gaps (Level 3), 9% managed (Level 4), and only 3% optimized (Level 5).
Steps completed, sources consulted, and evidence collected during the study.
Normative and theoretical framework: ISO/IEC 42001:2023 (AIMS — Annexes A, B, C, and D); ISO/IEC 23894:2023 (AI risk management); OECD AI Principles (2019, revised 2024); EU AI Act (2024/1689, high-risk systems).
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