AI Risk Register

An AI Risk Register is a living catalog of identified AI risks across the enterprise — each entry capturing risk description, likelihood, impact, mitigation status, and owner. Common risk categories include AI hallucination, prompt injection, data leakage, model drift, AI bias, IP infringement, regulatory non-compliance, vendor dependence, AI safety failures, and reputational harm. The register is updated continuously as new risks are identified and existing risks evolve. Mature AI governance frameworks tie the risk register to the AI use case registry — every use case maps to specific risks, and every risk maps to controls. The register feeds executive dashboards, AI ethics board agendas, and external disclosures. Tools include GRC platforms, AI governance suites, and increasingly purpose-built solutions like Centralpoint. AI risk management practice across regulated industries treats the register as the operational backbone of responsible AI — and as the natural complement to AI compliance evidence in any modern enterprise AI program.

Centralpoint Surfaces AI Risk Patterns in Real Time: Oxcyon's Centralpoint AI Governance Platform aggregates usage signals across OpenAI, Gemini, Llama, and embedded models. The platform meters consumption, captures audit logs, keeps prompts and skills on-premise, and embeds risk-aware chatbots into your portals with a single line of JavaScript.


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