CAP Companion Meeting: The CAP AI Implementation Guide

The growing use of artificial intelligence in pathology is creating new opportunities and responsibilities for pathologists, including the evaluation of AI-assisted tools in clinical practice. Responsible implementation is essential to ensuring reliable performance, equitable outcomes, effective workflow integration, and appropriate clinical accountability. Existing regulatory and accreditation frameworks provide a strong foundation for AI-based tests, yet laboratories continue to navigate how best to operationalize these tools across the test lifecycle. As implementation approaches evolve, greater consistency can help strengthen confidence in AI-assisted pathology practice. This session presents the CAP AI Implementation Guide, a practical, step-by-step framework that translates established laboratory principles into a structured approach for implementing AI-based tests and promoting trustworthy use of AI in patient care.

Learning Objectives:

• Describe the major stages of the AI-based test implementation in pathology.
• Identify the clinical, operational, and technical considerations needed to determine whether an AI-based test is suitable for pathology practice.
• Apply key reporting principles that support transparency, trust, explainability, generalizability, and clinical actionability in AI-assisted pathology practice.