Artificial intelligence has become an effective tool in software development, enabling students and developers to build applications and websites quickly and efficiently. However, an application functioning correctly does not necessarily mean it is secure or ready for deployment. AI-generated code may contain security vulnerabilities, including improper access control, exposure of user data, and inadequate validation of files and inputs. Therefore, code must undergo careful review and security testing before deployment, rather than being trusted simply because it works. Developers should also avoid sharing passwords, service keys, and sensitive information with AI tools, while verifying the sources of recommended software libraries. Human code reviews and automated security tools play an important role in identifying weaknesses and strengthening application protection. These practices are particularly important for cybersecurity students, who can use AI-generated code as a learning opportunity through analysis, testing in isolated environments, and understanding security mechanisms. Although artificial intelligence significantly reduces development time, building secure applications still requires understanding, careful review, and continuous testing. Ultimately, responsibility for system security remains with the developer.