AI-Powered Code Generation and Its Impact on Software Development

Artificial intelligence-driven code-generation tools have rapidly transformed modern software development. These systems assist developers by automatically generating functions, debugging programs, optimizing code quality, and supporting multiple programming languages. With the growth of large language models and deep-learning architectures, AI code generators now act as collaborative tools that enhance productivity rather than replace human programmers. This paper reviews the evolution, working principles, benefits, and limitations of AI-powered code generation systems published after 2020. It highlights real-world applications in software engineering, educational contexts, and automated testing environments. Key challenges involving accuracy, security risks, dependency, ethical concerns, and the need for human oversight are also examined. The review concludes with future research directions focused on improving reliability, reducing hallucinations, and developing responsible AI frameworks for software development.