Software development is undergoing a paradigm shift driven by Generative AI (GenAI), promised to revolutionize developer productivity. However, this rapid transformation risks exacerbating the long-standing challenge of technical debt. While current literature speculates on these risks, there is a critical absence of empirical, longitudinal evidence quantifying how widespread GenAI adoption is altering standard indicators of code quality. We address this gap through a longitudinal Interrupted Ti