Question for the webinar "Unleashing the Power of AI in Software Testing"

1- Automated Test Case Generation.
2- Defect Prediction.
3- Visual Testing and Validation.

Generate test cases

Generate test script

Compare visuals

These are some of the AI use cases which I have had hands on: 
1. Self-Healing AI as part of Vision AI
2. Test case/Test scenario generation from requirement documents.
3. Test plan estimation and automation savings
4. Started utilizing the TestCraft Browser extension for generating test ideas, accessibility testing and even generating some test code based on the element type. 

I'm maintaining the prompt base for all these and updating it based on the results. And I can see we need to even test the results of it - Won't trust the AI blindly :)
 

Here are three unique AI features that software testers can already utilize today:

1. Automated Test Case Generation Based on Application Behavior:
   AI can analyze application behavior patterns, user interactions, and workflows to automatically generate test cases that cover a wide range of scenarios. This feature helps identify test cases that might be missed during manual planning and ensures comprehensive coverage for complex applications.

2. AI-Driven Test Data Generation for Edge Cases:
   AI tools can intelligently generate diverse sets of test data, including edge cases and boundary conditions, which are often challenging to identify manually. This ensures that the application is tested against various input scenarios, improving test effectiveness without the need for manual data preparation.

3. Self-Healing Scripts for UI and Locator Changes:
   AI-powered testing tools can detect changes in the application's UI, such as updated locators or altered interface elements, and automatically adjust test scripts to accommodate these changes. This self-healing capability reduces maintenance time and ensures that test suites remain functional, even when the application evolves.