Skip to Content

How to Use AI in Test Automation in 2024

Tuukka Virtanen
Jan 23, 2024

Don’t procrastinate, now’s the time to experiment with new AI tools and explore how they can add value to your testing process.

AI tools are transforming the test automation landscape. Here, I’ve outlined some high-level ideas for enhancing your test automation capabilities with AI.

1. Generative AI in Test Case Generation

AI tools are already proficient in generating “happy path” test cases from text prompts, though human oversight is essential. New low-code/no-code platforms allow the generation of complete test cases from concise descriptions.

2. Generative AI in Test Data Generation

Creating a realistic, fresh, and anonymized test data set can be challenging. AI tools enable you to train them on your test data’s characteristics and reduce testing time and effort. While the most complex data requirements may still need manual configuration, AI helps in automating the bulk of the process.

3. Multimodal AI for Visual and Audio processing

Modern multimodal AIs can process video, image, voice, and sound data effectively, overcoming past challenges in automation. Utilizing these AIs for tasks like transcribing images to text simplifies visual testing and opens up new possibilities, such as processing natural language audio into a simplified text form.

4. Self-healing Test Automation

AI tools can now automatically identify, correct, and update minor bugs in your test scripts. After teaching an AI model about your system under test, it becomes capable of adapting tests to changes in the system. This can include automatically updating browser automation locators when they change, reducing maintenance efforts and saving development time.

5. AI Test Execution Prioritization

Prioritization is crucial in testing, determining which tests should be run and how frequently. AI tools analyze your test code base, considering factors like test criticality, coverage, execution time, path analysis, and code change frequency. This optimization ensures that critical tests and code lines are covered in less time, reducing test run times and allowing for more comprehensive testing possibilities.

These are just a few ideas for integrating AI tools into your testing process. AI-powered test automation tools are being introduced almost daily, with significant developments in this field.

If you aim to stay at the forefront of adopting these technologies, don’t wait for 2025—start now.

About the author

Tuukka Virtanen

Consultant | Finland
Test automation consultant with technical experience in test automation and quality assurance. TMap Next certified Test Engineer with knowledge in test planning and execution and test design techniques. Master of Science in Information Management. Indie game development as a side project. Creative and visual thinker.

    Leave a Reply

    Your email address will not be published. Required fields are marked *