AI-Augmented Software Engineering (AI-SE)

Abstract

Artificial Intelligence (AI) has significantly influenced various scientific andindustrial domains, and software engineering is no exception. AI-AugmentedSoftware Engineering (AI-SE) refers to the integration of artificial intelligence techniques into software development processes to enhance productivity, code quality, and decision-making. Modern AI-driven tools such as GitHub Copilot, Tabnine, and ChatGPT have transformed how developers write, test, debug, and maintain code. This paper presents a comprehensive review of AI-SE, discussing its evolution, core technologies, applications across the Software Development Life Cycle (SDLC), benefits, challenges, ethical considerations, and future research directions. The study also highlights the implications of AI-SE for education, industry practices, and collaborative development. While AI offers remarkable support in automating repetitive tasks and improving efficiency, concerns related to reliability, bias, intellectual property, and over dependence remain significant. The paper concludes that AI-SE will not replace software engineers but will redefine their roles, shifting focus from manual coding to design thinking, validation, and governance. KEYWORDS: Artificial Intelligence, Software Engineering, MachineLearning, Code Generation, DevOps, AI-Augmented Development,Automation