Using AI/ML and Production Data to Improve Software Testing` AI and ML are two related but distinct concepts that emphasize the creation of machines with intelligent capabilities, and the use of large datasets to drive decision-making. In software testing, AI and ML can be used to gather production user data to generate smarter regression tests, reducing the burden of manual testing and improving system quality. By leveraging production data, companies can automate test generation, reduce guessing on how to test their systems, and provide a better end-user experience. However, building algorithms that can interpret this data intelligently requires significant upfront effort, but the potential payoffs justify the investment. As AI/ML technologies continue to evolve, incorporating them into software testing routines will become increasingly important for organizations looking to stay ahead in the industry.