AI Glossary
AI Assurance
AI Assurance is the process of evaluating AI systems to provide confidence that they are trustworthy, secure, compliant, and operating as intended.
AI Assurance
Overview
Organizations increasingly need confidence that their AI systems operate as intended.
Providing that confidence is the goal of AI Assurance.
AI Assurance is the process of evaluating and providing confidence that AI systems are trustworthy, reliable, secure, compliant, and operating as intended.
AI assurance brings together multiple governance activities, including:
- Risk assessments
- AI audits
- Security reviews
- Model validation
- Documentation
- Continuous monitoring
- Compliance verification
A helpful way to think about AI assurance is a vehicle safety inspection.
Before a vehicle is approved for the road, inspectors verify that critical systems function properly.
AI assurance performs a similar role by providing confidence that AI systems are ready for deployment and ongoing operation.
AI assurance supports AI Governance by helping organizations demonstrate responsible AI practices to executives, regulators, customers, and other stakeholders.
Why It Matters
AI assurance builds confidence that AI systems are operating responsibly while helping organizations reduce risk, improve transparency, and strengthen governance.
Real-World Example
Before deploying a new AI-powered hiring system, an organization completes an AI assurance review that includes fairness testing, security assessments, documentation reviews, governance approvals, and ongoing monitoring requirements.
Related Concepts
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- AI Governance vs AI Risk Management
- Why AI Governance Matters As AI Adoption Grows