What is Acceptance Criteria?

Explained

Acceptance criteria translate requirements into observable checks—e.g., schema validity, golden answers, safety gates. For AI systems they underpin eval harnesses, regression suites, and human-in-the-loop review, linking specs to measurable quality.

Further reading

• AI Fairness Monitoring: From Defensive Cost to Strategic Advantage
• Ethical AI: Building Responsible AI Experiences for Enhanced User Trust

Related terms

• Human-in-the-Loop Design where humans supervise or correct AI decisions.
• AI Bill of Materials Inventory of model lineage, datasets, dependencies, and licenses for an AI system.
• AI Governance Framework of policies, processes, and controls for responsible and ethical AI use in the enterprise.
• AI Native Architecture and processes designed from the ground up for AI, not as an afterthought.
• CRM System for managing customer relationships; AI augments it with prediction and automation.
• CX Customer experience; AI enables personalization and automation at scale.