Artificial intelligence (AI) is poised to revolutionise many aspects of technology, including how we test and validate new IT systems before deployment. As AI capabilities grow more advanced, AI-based tools have the potential to automate and enhance many test processes that are currently manual and time-consuming. Let's explore some of the key ways AI could impact testing in the near future.

Automated Test Case Generation

One of the most tedious and error-prone aspects of testing is creating comprehensive test cases that cover all the required scenarios and use cases for a system. AI techniques like natural language processing, machine learning and fuzzy logic can help automatically generate test cases by analysing system requirements, user stories and other design documents.

By leveraging AI to create test cases, testers can focus their efforts on high-value testing tasks instead of manual test creation. AI-generated tests also provide complete coverage and consistency, preventing gaps or overlaps in testing.

Intelligent Test Data Generation

Generating and managing test data is another demanding task for testing teams. Test data needs to be realistic and cover edge cases to identify defects. For large systems, this can mean creating millions of data rows to feed into system tests.

AI algorithms can intelligently and automatically generate complex test data sets. By applying constraints and business rules, AI can produce data that covers different use cases and meets parameters like data randomness, masking, and correlation across fields. This saves significant time compared to manual test data creation.