This project report titled “AI in Software Development” presents a comprehensive study on the impact of generative Artificial Intelligence tools in modern software engineering workflows. The work evaluates widely used AI-assisted development tools such as ChatGPT, GitHub Copilot, Amazon CodeWhisperer, and Tabnine, focusing on their influence on developer productivity, code quality, maintainability, and security. The study combines controlled experiments, static code analysis, repository mining, and developer feedback to compare AI-assisted coding with traditional manual development approaches. Key performance indicators such as task completion time, bug density, Maintainability Index, cyclomatic complexity, and security vulnerabilities are analyzed across multiple programming environments. Results indicate that AI tools significantly improve development speed and reduce cognitive effort, but may introduce higher logical error rates, inconsistent coding practices, and subtle security risks if used without proper review. The report also proposes best practices, risk mitigation strategies, and guidelines for safely integrating generative AI into professional software development lifecycles. This work is submitted in partial fulfillment of the requirements for the award of Bachelor of Technology in Computer Science & Engineering at JECRC University, Jaipur, for the academic year 2025–2026, and is intended for students, researchers, and professionals interested in AI-driven software engineering.