What Are AI Testing Tools?
AI testing tools use artificial intelligence, machine learning, or generative AI to assist with software testing activities.
Depending on the tool, they can help you:
- Generate test cases from requirements.
- Create automation scripts.
- Identify missing test scenarios.
- Analyze test failures.
- Generate test data.
- Support API testing.
- Compare user interfaces visually.
- Reduce repetitive testing activities.
AI tools do not guarantee that every test will be correct. QA engineers must review the generated output and validate the actual application behavior.
1. ChatGPT – An AI Assistant for QA Engineers
ChatGPT can help QA engineers understand testing concepts, create test scenarios, write automation scripts, and investigate errors.
You do not need to be an expert programmer to begin using it. You can describe your testing requirement in simple English and ask for guidance.
How QA engineers can use ChatGPT:
- Generate positive and negative test scenarios.
- Create test cases from user stories.
- Prepare test data.
- Explain SQL queries and automation code.
- Draft bug reports.
- Analyze error messages.
- Prepare interview questions for QA roles.
Practical example:
Suppose you are testing a login page. You can use this prompt:
Sample prompt:
“Act as an experienced QA engineer. Create positive, negative, boundary, and security-related test scenarios for a login page. Include the scenario, test steps, expected result, and priority in a table.”
ChatGPT can generate an initial set of scenarios that you can review and improve based on the application requirements.
Best for: Manual testers, beginners, QA leads, and automation engineers.
2. GitHub Copilot – AI Assistance for Automation Coding
GitHub Copilot helps developers and automation testers write and understand code. Depending on the supported features and development environment, it can suggest code, explain existing scripts, and assist with debugging.
For QA engineers learning Playwright with TypeScript, it can be particularly useful.
How QA engineers can use GitHub Copilot:
- Generate Playwright test script drafts.
- Explain TypeScript syntax.
- Suggest assertions and locators.
- Create reusable helper functions.
- Help investigate coding errors.
- Improve code readability.
Practical example:
Imagine that you need to automate a login scenario using Playwright.
You can ask:
“Create a Playwright test using TypeScript for a login page. Enter a valid username and password, click the login button, and verify that the dashboard is displayed. Explain each line of code.”
Review the generated script, verify that the locators match your application, and execute the test before using it in your project.
Best for: Playwright, Selenium, TypeScript, JavaScript, and other coding-based automation workflows.
3. Playwright Test Agents – AI-Assisted Browser Testing
Playwright is a popular framework for browser automation. Its Test Agents feature includes three agents designed for different testing activities: Planner, Generator, and Healer.
These agents can support the creation and maintenance of automated browser tests. Their capabilities depend on the configured development environment and project setup.
How QA engineers can use Playwright Test Agents:
- Explore application flows and prepare test plans.
- Turn test plans into Playwright test files.
- Execute tests and help repair failing tests.
Practical example:
For an e-commerce website, you might start with this request:
“Create a test plan for searching for a product, adding it to the cart, updating the quantity, and completing checkout.”
An AI-assisted workflow can help convert the plan into automated tests. You must still verify the assertions, test data, and business rules.
Best for: QA automation engineers working with Playwright.
4. Postman AI Features – Smarter API Testing
API testing is an important part of software quality assurance. Postman provides AI-assisted features that can help testers work with APIs using natural-language instructions and supported workflows.
How QA engineers can use Postman AI features:
- Understand API requests and responses.
- Assist with creating and updating tests.
- Investigate request failures.
- Work with API specifications.
- Support API workflow automation.
Practical example:
Suppose you are testing a user registration API.
You can ask an AI assistant to help design scenarios for:
- Successful registration.
- Missing required fields.
- Invalid email addresses.
- Duplicate email addresses.
- Invalid authentication.
- Incorrect data types.
- Unexpected server errors.
For each scenario, verify the status code, response body, error message, and relevant business rules.
Remember that an HTTP 200 response alone does not prove that the API behaves correctly.
Best for: Manual API testers, automation engineers, and testers learning API testing.