The excuse “we don’t have time to write tests” doesn’t hold up anymore. AI has reshaped the way teams approach software testing, making it faster, smarter, and more accessible than ever. Tools like GitHub Copilot, ChatGPT, and Applitools Autonomous can generate reliable automated tests without slowing down your development flow.
If you’ve ever struggled with limited testing resources or hesitated to adopt AI-enhanced workflows, now is the perfect time to embrace AI-powered testing.
How GitHub Copilot Helps Accelerate Unit Test Creation
GitHub Copilot can dramatically speed up unit test creation. It can generate unit tests directly in your editor with a single prompt. For example, typing “create unit tests for Hello.tsx” in VS Code can instantly produce functional test cases using React Testing Library.
While Copilot’s first drafts were impressive—correctly using accessible locators and matching key UI elements—it’s important to note that AI-generated tests often require slight refinements.
Expecting a one-shot from AI is probably unrealistic—but in my experience, it gets you pretty darn close.
Copilot typically picks up on your dependencies, infers structure, and outputs readable, executable tests. If the results aren’t perfect, for instance, using fragile selectors or inconsistent naming, you can quickly iterate. Adjusting your prompt often resolves these issues. In many cases, reprompting is faster than manual edits.
Accessible locators and consistent naming can be enforced through clearer prompting or by storing preferences in a centralized configuration file
The key? Good prompts make a big difference. Prompting Copilot to use best practices, like favoring accessible selectors, resulted in much cleaner and more reliable output.
Taking Testing Further with Playwright and Copilot
Beyond unit tests, AI can support end-to-end testing for full user flows. Using Copilot with a framework like Playwright, you can prompt test generation by simply referencing a live URL and desired interactions.
For example, pointing Copilot to a public demo app like TodoMVC and requesting end-to-end tests will often result in tests for adding, completing, deleting, and filtering tasks—all without writing code manually.
To further improve coverage, ChatGPT can help by generating a requirements document for the app. This doc acts as a guide to ensure tests align with expected behaviors.
The better the input we provide the LLM, the better output we’re likely to get. A requirements doc is a really important piece of input.
Once the requirements are defined, you can direct the AI to use them when generating tests, producing more complete and targeted coverage. Just remember to include your preferences for things like locator strategy and naming conventions in your prompt or project config.
The message is clear: Combining ChatGPT and Copilot creates a powerful AI-assisted workflow for test generation. This approach cuts down on manual scripting while improving test depth.
Boosting End-to-End Testing with Applitools Autonomous
Applitools Autonomous handles creating automated tests with AI differently. Instead of writing code or interacting with the DOM, you provide a URL, and the system automatically scans the app. It generates visual and functional tests and organizes results into a centralized dashboard.
Highlights of what Autonomous can do include:
- Crawl an entire application from just a URL and automatically generate visual and functional tests
- Use plain English commands to create, edit, and validate tests (no coding needed)
- Validate UI, behavior, and API responses in one workflow
- Capture dynamic data like confirmation IDs, verify API responses, and support parameterization without code
Unlike traditional recording tools, Autonomous intelligently builds stable, scalable tests while seamlessly validating across browsers. It even flags hidden 404 errors—showcasing the tool’s ability to catch issues early.
Another key point is that anyone, regardless of technical background, can create sophisticated tests using natural language. At the same time, it maintains the depth and flexibility senior developers demand.
Key Takeaways for Modern Testing Workflows
Today’s AI software testing tools are designed for real-world developer needs:
- Copilot accelerates unit and E2E test creation with natural language prompts.
- ChatGPT fills documentation gaps by drafting requirements for better test coverage.
- Applitools Autonomous redefines E2E testing, combining visual validation and functional flows—from UI to visual to API—and plain-English test authoring. It integrates these into a single, no-install SaaS platform.
AI doesn’t replace the tester’s critical thinking — it augments your workflow, helping you focus on improving test quality, not just checking boxes.
In Summary…
The landscape of automated testing is still evolving. With tools like Copilot, ChatGPT, and Applitools Autonomous, building and maintaining high-quality automated tests no longer has to be a slow, painful process. Whether you’re a front-end engineer, QA lead, or tech manager, adopting AI-powered workflows will free up your team’s time. It will increase your confidence in releases and bring better quality to every sprint.
🎥 Want to learn more about how to create automated tests with AI? Watch the full session on demand to see in-depth demos.
Quick Answers
Absolutely. AI-powered tools make end-to-end (E2E) testing faster and more comprehensive:
– GitHub Copilot can generate E2E tests in Playwright by simply referencing a live app URL and describing the intended user interactions—like adding or deleting tasks in a to-do app.
– ChatGPT strengthens the process by drafting a requirements document based on app functionality, which guides test creation and ensures behavior-driven coverage.
– Applitools Autonomous takes it a step further by auto-generating both visual and functional E2E tests from a single URL—no code required. It scans the application, creates tests based on real user flows, and validates UI and API responses. The platform also supports natural language test commands, making advanced E2E testing accessible even to non-developers.
Together, these tools create a robust, AI-enhanced workflow that minimizes manual scripting and maximizes test depth, speed, and reliability.
Combining these tools creates a powerful AI testing stack:
– Copilot quickly builds unit and E2E tests.
– ChatGPT generates requirements for better planning.
– Applitools Autonomous adds full-scale, no-code testing with visual validation.
AI-generated tests are often surprisingly close to production-ready. However, minor refinements—such as improving selector stability or renaming variables—are typically needed. Clear prompts and centralized configuration files help standardize and improve output.
Applitools Autonomous auto-generates functional and visual tests by crawling your app from a provided URL. It supports natural language commands, verifies UI and API responses, and doesn’t require code, making it ideal for both technical and non-technical users. Teams can try it out for free right here.
AI-powered tools integrate smoothly into agile workflows by:
– Speeding up test creation.
– Reducing technical debt from manual scripting.
– Enabling continuous validation during CI/CD.
– Freeing up developers to focus on improving coverage and quality rather than writing repetitive tests.
