"Improving overall quality" with AI and ML in automated testing means:

1. _Defect reduction_: AI and ML help reduce defects, improving overall quality.

2. _Increased reliability_: AI and ML improve system reliability, reducing downtime.

3. _Enhanced performance_: AI and ML optimize system performance, improving user experience.

4. _Improved security_: AI and ML detect and prevent security vulnerabilities, ensuring system integrity.

5. _Better decision making_: AI and ML provide data-driven insights, enabling informed decisions.

6. _Streamlined processes_: AI and ML automate and optimize testing processes, improving efficiency.

7. _Improved customer satisfaction_: AI and ML help deliver high-quality products, improving customer satisfaction.

8. _Competitive advantage_: AI and ML enable organizations to innovate and stay ahead of the competition.

By improving overall quality, AI and ML in automated testing enable organizations to deliver high-quality products faster, reducing costs, improving customer satisfaction, and gaining a competitive advantage in the market.