AI Glossary
AI Risk Assessment
An AI Risk Assessment is the process of identifying, evaluating, and documenting potential risks associated with an AI system.
AI Risk Assessment
Overview
Before launching a new product, organizations often evaluate potential risks.
They may assess financial risks, operational risks, legal risks, or security risks.
AI systems require a similar approach.
An AI Risk Assessment is a structured process used to identify, evaluate, and document risks associated with an AI system.
A useful analogy is inspecting a bridge before allowing traffic to cross.
Engineers examine possible weaknesses to reduce the likelihood of future problems.
AI risk assessments serve a similar purpose.
They help organizations identify issues before they become significant incidents.
An AI risk assessment may evaluate:
- Privacy risks
- Security risks
- Compliance concerns
- Bias and fairness issues
- Data quality problems
- Operational impacts
- Reputational risks
The purpose is not to eliminate every possible risk.
That is rarely achievable.
Instead, the goal is to understand risks and determine appropriate safeguards.
Organizations often perform risk assessments before deploying AI systems and periodically afterward as systems evolve.
As AI adoption continues expanding, risk assessments have become one of the most common tools used within governance and compliance programs.
Why It Matters
Risk assessments help organizations make informed decisions, prioritize resources, reduce uncertainty, and improve the overall safety and reliability of AI systems.
Real-World Example
A company plans to deploy an AI-powered hiring tool.
Before deployment, it conducts an assessment to evaluate potential bias, privacy concerns, and compliance requirements.
This review is an AI risk assessment.
Related Concepts
- AI Governance
- AI Risk Management
- AI Audit
- AI Compliance Framework
- Data Governance
- Model Documentation