Example Concept: AI-driven code analysis tools, like Amazon Q or GitHub Copilot, can automatically identify code issues, suggest improvements, and enforce coding standards. However, they may require adjustments to existing workflows, such as integrating new tools into CI/CD pipelines or retraining developers to interpret AI-generated suggestions. Additionally, AI tools can sometimes produce false positives or suggestions that conflict with project-specific guidelines, necessitating a balance between automated insights and human judgment.