ABSTRACT: Generative Artificial Intelligence (AI) has rapidly evolved into a transformative force within the software industry, reshaping how developers write, test, document, and maintain code. Tools such as GitHub Copilot, ChatGPT, Amazon CodeWhisperer (now Amazon Q Developer), and Google Gemini Code Assist leverage large language models trained on vast code repositories to generate functional code snippets, suggest bug fixes, and automate repetitive engineering tasks. This review paper examines the impact of Generative AI on software development productivity, with particular attention to coding speed, code quality, debugging efficiency, documentation, and overall developer experience. The study is based on secondary data drawn from peer-reviewed journals, industry reports, conference proceedings, and case studies published by technology organizations. The paper further investigates the benefits, limitations, and ethical considerations associated with the adoption of Generative AI in software engineering, along with its likely future trajectory in the global and Indian software industry.
KEYWORDS: Generative AI, Software Development Productivity, Large Language Models, AI Pair Programming, Code Generation, Software Engineering, Developer Experience.
IMPACT OF GENERATIVE AI ON SOFTWARE DEVELOPMENT PRODUCTIVITY
SATYAVAN HARINATH RAJBHAR
SHREE RAM COLLEGE OF COMMERCE, BHANDUP.