What is AI unit testing?

This episode of Techsplainers explores AI unit testing and how artificial intelligence can support one of software development’s most common quality practices. Building on the earlier episodes about shift-left security and static code analysis, it explains how unit tests check small pieces of code in isolation and how AI can help generate test cases, identify edge conditions, improve coverage and maintain tests as code changes. The episode also clarifies an important distinction between using AI to help test traditional software and testing software components that themselves rely on AI models or probabilistic outputs. Along the way, it examines the practical benefits of faster test creation, broader scenario coverage and stronger support for continuous development workflows. It also addresses the limits of AI-generated tests, including shallow assertions, duplicated assumptions, brittle test suites and the continued need for human review. Finally, the episode places AI unit testing within a larger development strategy that includes code analysis, debugging and secure review practices. Find more information at https://www.ibm.com/think/topics/ai-unit-testing Find all the Techsplainers episodes here https://www.ibm.biz/techsplainers-podcast Narrated by Ian Smalley