# Ai Risk Management
**Source:** https://glossary.keenfunnel.com/terms/ai-risk-management
**Language:** Arabic

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## شرح تقني

AI risk management applies throughout the lifecycle and combines organisational governance with system-level analysis. It examines context, stakeholders, intended and foreseeable uses, data and model limitations, security, safety, reliability, transparency, fairness, privacy, and third-party dependencies. The NIST AI RMF organises activities into Govern, Map, Measure, and Manage; ISO/IEC 23894 provides AI-specific risk-management guidance.

## الأهمية التجارية

The practice helps organisations prioritise controls, make deployment decisions, allocate accountability, satisfy assurance expectations, and reduce legal, operational, reputational, and societal harm.

## مثال على التنفيذ

A lender maps the context of an AI-assisted credit process, measures performance and bias across relevant groups, implements human review and appeal controls, monitors drift, and records residual risk acceptance.

## القيود والمفاهيم الخاطئة الشائعة

AI risk cannot be reduced to a single score. Risk depends on use context and affected stakeholders, and some impacts are difficult to quantify. Compliance with a framework does not automatically establish legal compliance or acceptable residual risk.

## المواضيع

حوكمة الذكاء الاصطناعي الأمن السيبراني هندسة البيانات

## المصادر

NIST AI RMF 1.0 — ISO/IEC 23894:2023 — https://www.iso.org/standard/77304.html

## ناقش أنظمتك

هل تحتاج إلى مساعدة في تنفيذ هذا المفهوم أو تقييمه؟ تقوم Keenfunnel بتصميم أنظمة الذكاء الاصطناعي المتصلة والأتمتة والبيانات.

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