Artificial Intelligence (AI) has emerged as a transformative force across multiple sectors, including software engineering, where its integration represents a significant paradigm shift in how software systems are conceived, developed, managed, and maintained. The adoption of AI technologies is reshaping industry practices, redefining developer roles, and altering required skill sets. This paper examines the multifaceted impact of AI on software engineering, with particular emphasis on improvements in development efficiency, software quality, project management, and the democratization of software development. Using a conceptual and analytical approach grounded in existing literature and practical observations, the study explores how AI-driven technologies, such as Generative AI, Large Language Models, and intelligent automation, are transforming key stages of the software development lifecycle. The analysis reveals that AI-enhanced tools significantly improve productivity, reduce time-to-market, and enable innovative development practices, including automated code generation, intelligent testing and debugging, adaptive systems, and broader participation by non-technical stakeholders. However, the findings also highlight critical challenges associated with AI adoption, including over-reliance on automated systems, ethical and legal concerns, security vulnerabilities, and the potential erosion of core software engineering skills. The paper concludes that AI is not replacing software engineers but augmenting their capabilities, necessitating a balanced and responsible integration that combines human oversight, ethical governance, and continuous skill development to fully realize the benefits of AI-driven software engineering.
Bada et al. (Fri,) studied this question.
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