Home Assessing and Validating AI Applications in Quality Systems AI application validation series
Assessing and Validating AI Applications in Quality Systems A practitioner series for defining, assessing, testing, releasing, and maintaining AI applications used in Quality and regulated processes.
Series method
Begin with the work, not the model Define the decision. State what work changes and what could be affected by an incorrect or incomplete result. Draw the application boundary. Include information sources, processing components, interfaces, people, outputs, and connected systems. Keep authority explicit. Separate generated information from review responsibility, final decisions, and permitted actions. Published chapters
Start with intended use Chapter 1 establishes the scope needed for later risk assessment, requirements, testing, release, and monitoring decisions.
01
Foundation · 18 minutes
Define the application boundary, permitted functions, operating conditions, human responsibilities, exclusions, and reassessment triggers before risk assessment or testing begins.
Four original application and workflow diagrams Supplier-assessment and validation-record examples Practice exercise with a suggested answer Read the complete chapter How this section relates to the Academy This is a separate long-form practitioner series. The AI Assurance Academy remains the structured 20-chapter learning path. Examples in this series are fictional educational workflows and do not describe an employer, client, or validated product.