{"product_id":"ags-ai-governance-policy-management-system-package","title":"AI Governance Policy \u0026 Management System Package","description":"\u003cp\u003e\u003cem\u003eAn artificial intelligence management system your board, your auditor and your regulator can all read from the same controlled source.\u003c\/em\u003e\u003c\/p\u003e\n\u003ch2\u003eOverview\u003c\/h2\u003e\n\u003cp\u003eISO\/IEC 42001 is the management system standard for artificial intelligence, and this package is built to its structure: an AI management system (AIMS) across seven governance domains, with terminology from ISO\/IEC 22989, risk practice aligned to the NIST AI Risk Management Framework, and ethical requirements traceable to the OECD AI Principles.\u003c\/p\u003e\n\u003cp\u003eValidation is the gate. A model is not relied upon until someone has established what it was built to do, on what data, against which thresholds and known limitations, and has accepted it on the record. An AI risk is scored the same way whether the system was built in-house or procured, so exposures can be ranked and given controls with a residual rating. Deployed systems stay in view through monitoring indicators with targets and named owners, and a twelve-month review cycle is built in. A master index, \u003cstrong\u003eAGS-AI-MS-000\u003c\/strong\u003e, holds the domains together under the AGS-AI numbering convention.\u003c\/p\u003e\n\u003ch2\u003eWhat this system covers\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eAI governance structure — accountability, ownership and board-level oversight of AI use.\u003c\/li\u003e\n\u003cli\u003eResponsible AI — the OECD AI Principles turned into stated requirements for the systems an organisation builds, buys and runs.\u003c\/li\u003e\n\u003cli\u003eAI risk management — identification, scoring, controls and residual ratings, aligned to the NIST AI Risk Management Framework.\u003c\/li\u003e\n\u003cli\u003eAI ethics — the ethical requirements a use case has to meet, and the periodic checks that verify it still does.\u003c\/li\u003e\n\u003cli\u003eAI data — governance of the data AI systems consume, including retention and ownership of what is kept.\u003c\/li\u003e\n\u003cli\u003eAI model validation — what must be established about a model, and by whom, before it is put to work.\u003c\/li\u003e\n\u003cli\u003eAI monitoring — continued oversight of deployed systems, measured against indicators with targets and owners.\u003c\/li\u003e\n\u003cli\u003eShared terminology from ISO\/IEC 22989, so governance, risk and engineering describe the same things the same way.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eWho it's for\u003c\/h2\u003e\n\u003cp\u003eWhen an ISO\/IEC 42001 project starts, when a regulator asks how AI use is controlled, or when the board wants assurance in writing, the work lands on chief AI officers, compliance and risk teams and IT governance functions in organisations that build, deploy or procure AI. The documents are editable throughout, so the framework ends up describing your own AI estate and the people accountable for each part of it.\u003c\/p\u003e","brand":"Apex Global Solutions AGS","offers":[{"title":"Default Title","offer_id":56792708579668,"sku":"AGS-01-023","price":790.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1052\/4996\/4372\/files\/AGS-01-001_AI_Governance_Policy.png?v=1786639545","url":"https:\/\/agskits.com\/products\/ags-ai-governance-policy-management-system-package","provider":"Apex Global Solutions","version":"1.0","type":"link"}