The integration of Artificial Intelligence (AI) into software development is revolutionizing how code is written, optimized, and debugged. AI-powered tools are capable of automating code generation, identifying and fixing bugs, and enhancing development efficiency. This research explores the future of AI in software development, focusing on its impact on automating code generation and debugging. We analyze various AI-driven tools such as GitHub Copilot, OpenAI Codex, and Deep Code to understand their effectiveness in enhancing productivity and reducing human errors. The findings suggest that while AI significantly streamlines software development, challenges such as ethical concerns, code security, and AI interpretability must be addressed. This study provides insights into the advantages, limitations, and future directions of AI in software development.
AI, software generation, development, debugging, code automation, machine learning, deep learning.