Yes, TDD can be used for AI, machine learning, and modern tech solutions, but with a practical approach. TDD means writing tests before writing actual code. This TDD approach works well in modern systems where reliability and correctness are important. To understand clearly, what is test driven development is a method where developers first define expected behavior through tests, then build code to pass those tests. In AI and machine learning projects, TDD development is mainly used for data pipelines, APIs, model inputs, outputs, and logic validation. While model predictions may change, core functions can still be tested, showing clear benefits of TDD such as fewer bugs, cleaner code, and easier updates. These are strong advantages of test driven development, especially in fast-changing modern tech environments. Conclusion: TDD is not limited to traditional software. When applied correctly, it supports AI, machine learning, and modern solutions by improving code quality, stability, and long-term maintainability.