"Domain expertise integration" with AI and ML in automated testing means:

1. _Subject matter expert (SME) input_: SMEs provide domain knowledge and expertise to AI and ML models.

2. _Business context understanding_: AI and ML models are trained to understand business context, requirements, and goals.

3. _Industry-specific knowledge_: AI and ML models are infused with industry-specific knowledge and best practices.

4. _Customized model development_: AI and ML models are developed or customized to meet specific business needs.

5. _Human-AI collaboration_: Humans and AI/ML models collaborate to develop test cases, scenarios, and scripts.

6. _Domain-specific data curation_: Data relevant to the specific domain is curated and used to train AI/ML models.

7. _Model validation and feedback_: SMEs validate AI/ML model performance and provide feedback for improvement.

8. _Continuous refinement_: AI/ML models are continuously refined and updated based on SME feedback and changing business needs.

By integrating domain expertise with AI and ML capabilities, automated testing can:

- Improve test accuracy and relevance

- Enhance business alignment and value

- Reduce false positives and negatives

- Increase trust in AI/ML-driven testing

- Support continuous improvement and refinement