AI Governance

AI Governance is the framework of policies, roles, controls, and processes an organization uses to manage AI responsibly across its lifecycle — from idea to retirement. Mature AI governance includes AI policy documents, ownership structures (AI ethics boards, AI centers of excellence), inventory and registry of AI systems, model documentation requirements, AI risk management procedures, audit trails, approval workflows, and incident-response plans. International standards like ISO/IEC 42001 (AI management systems) and frameworks like the NIST AI Risk Management Framework codify governance practices. Regulations including the EU AI Act, the U.S. Executive Order on AI, and sector rules in healthcare and finance impose specific governance requirements. Real-world examples include Microsoft's Responsible AI Standard, Google's AI Principles, and IBM's AI Ethics Board. Effective AI governance is now a board-level concern for every enterprise AI program — and is the foundation of AI compliance and trustworthy AI deployment.

Centralpoint IS the AI Governance Platform: Oxcyon built Centralpoint as the operational backbone of enterprise AI governance. Model-agnostic across OpenAI, Gemini, Llama, and embedded models, Centralpoint meters every LLM call, stores prompts and skills strictly on-premise, and embeds governed chatbots across any portal with a single line of JavaScript. Governance becomes operational, not aspirational.


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