Impact of Generative AI on the Software Development Lifecycle

Generative Artificial Intelligence (GenAI) has emerged as one of the most transformative technologies in the field of software engineering. Its ability to automate code generation, documentation, testing, and architectural design is redefining traditional workflows across the Software Development Lifecycle (SDLC). This study explores the qualitative impact of GenAI on development processes, team dynamics, productivity, quality assurance, and decision-making. Through thematic analysis of existing literature and expert perspectives, the research identifies how GenAI accelerates development while simultaneously introducing new challenges related to trust, model reliability, ethical use, and skill dependencies. The findings show that GenAI acts as a powerful collaborator by automating repetitive and time-intensive tasks, enhancing developer efficiency, and supporting high-level decision-making. However, AI-generated outputs may contain inaccuracies, introduce security vulnerabilities, or lead to over-reliance among developers. Concerns also arise regarding intellectual property, data privacy, and responsible AI governance. This paper concludes that GenAI will not replace developers but will redefine the nature of software engineering through hybrid human–AI collaboration. The study also highlights the necessity of developing regulatory frameworks, AI literacy programs, and transparent evaluation systems to ensure the safe and effective future integration of GenAI in SDLC.