How do you see the use of AI in QA work globally, within the framework of process improvement?

AI in QA can significantly improve processes through automation and enhanced testing quality:

• Automatic test case generation based on requirements analysis and code.
• Intelligent analysis of test results, identifying anomalies and non-standard failures.
• Test coverage optimization — AI helps identify the most critical scenarios for testing.
• Automation of routine tasks — for example, creating test data, setting up environments.
• Early defect detection through log analysis and application behavior.

Overall, AI contributes to reducing testing time, minimizing human errors, and increasing product stability. However, it is important to maintain control and expertise of QA engineers to correctly interpret results and manage the process.