Freeman, Laura J.Robert, JohnWojton, Heather2025-08-122025-08-122025-06-23https://hdl.handle.net/10919/137470Generative Artificial Intelligence (GenAI) is transforming software development processes, including test and evaluation (T&E). From automating test case design to enabling continuous testing in DevOps pipelines, AI-driven tools enhance the efficiency, accu-racy, and speed of software testing. At the same time, the integra-tion of AI components into software-reliant systems introduces new challenges for verification and validation (V&V). Traditional T&E methodologies must evolve to address issues such as AI bias, hal-lucinated outputs, and the complexity of validating non-determin-istic behaviors. This position paper examines how existing T&E methods must evolve to account for AI’s stochastic nature, and con-versely how GenAI is transforming T&E practices across the soft-ware development lifecycle (SDLC).application/pdfenCreative Commons Attribution 4.0 InternationalArticle - Refereed2025-08-01The author(s)https://doi.org/10.1145/3696630.3728723