{"slug":"south-korea-ai-basic-act-art-32-safety-measures-for-high-performance-ai","id":"AIPT-OBL-0062","permanent_url":"https://aipolicytracker.org/id/AIPT-OBL-0062","title":"Operators of AI above the compute threshold must run lifecycle risk management and report safety results","short_title":"Safety of high-performance AI","category":"safety_testing","summary":"An AI business operator whose AI system's cumulative training computation exceeds the threshold set by Presidential Decree must identify, assess and mitigate risks across the system's life cycle, build a risk management system to monitor and respond to safety incidents caused by the AI, and submit the results of these measures to the Minister of Science and ICT. The threshold and reporting form are set in the Decree.\n","practical_action":"Track training compute against the decree threshold and prepare a safety report covering risk identification, mitigation and incident monitoring for submission to the ministry.\n","is_binding":true,"applies_from":"2026-01-22","section":null,"source_reference":"Article 32","official_source_url":"https://www.law.go.kr/lsInfoP.do?lsiSeq=268543","review_status":"verified","confidence_level":"medium","last_verified_at":"2026-09-26","reviewed_by":"Bhaskar Bhatt","actors":["provider","gpai_provider"],"sectors":["cross_sector"],"use_cases":["generative_ai"],"applicability":[{"description":"Operators of AI systems whose cumulative training compute exceeds the Presidential Decree threshold, in practice frontier-scale model developers.","actors":["provider","gpai_provider"],"conditions":null}],"evidence_examples":[{"title":"Lifecycle risk assessment and mitigation record","description":null,"artifact_type":"report"},{"title":"Safety measures report submitted to the ministry","description":null,"artifact_type":"report"}],"framework_mappings":[{"framework":"nist_ai_rmf","framework_name":"NIST AI RMF 1.0","reference":"MAP 5.1, MEASURE 2.6, MANAGE 1.3, MANAGE 4.3","note":"Safety evaluation, risk treatment and incident response.","confidence_level":"medium","is_original":true},{"framework":"iso_42001","framework_name":"ISO/IEC 42001:2023","reference":"Clause 6.1.2, 6.1.3, 9.1","note":"Risk assessment, treatment and monitoring.","confidence_level":"medium","is_original":true}],"controls":[{"slug":"frontier-model-safety-framework","title":"Frontier model safety and security framework","kind":"policy","relationship":"satisfies","note":"Compute tracking, lifecycle risk assessment and reporting to the authority.","confidence_level":"medium","url":"https://aipolicytracker.org/controls/frontier-model-safety-framework"},{"slug":"genai-red-team-testing","title":"Adversarial and red-team testing for generative AI","kind":"technical","relationship":"supports","note":"Evidence for the risk identification step.","confidence_level":"medium","url":"https://aipolicytracker.org/controls/genai-red-team-testing"},{"slug":"ai-incident-management-and-reporting","title":"AI incident management and regulatory reporting","kind":"process","relationship":"supports","note":"Incident monitoring and response arm of the risk management system.","confidence_level":"medium","url":"https://aipolicytracker.org/controls/ai-incident-management-and-reporting"}],"url":"https://aipolicytracker.org/obligations/south-korea-ai-basic-act-art-32-safety-measures-for-high-performance-ai","policy":{"slug":"south-korea-framework-act-on-the-development-of-artificial-intelligence-and-establishment-of-a-foundation-for","title":"Framework Act on the Development of Artificial Intelligence and Establishment of a Foundation for Trust (AI Basic Act, Act No. 20676)","status":"in_force","jurisdiction":"south-korea","url":"https://aipolicytracker.org/policies/south-korea-framework-act-on-the-development-of-artificial-intelligence-and-establishment-of-a-foundation-for"}}