Artificial intelligence (AI) tools are increasingly integrated into modern software development workflows, assisting developers in tasks such as code generation, testing, and debugging. This study presents a comparative evaluation of three AI-assisted development tools - Cursor, GitHub Copilot, and Gemini - with a focus on their effectiveness in frontend development. The comparison was conducted through practical experimentation within a small-scale Vue 3 project, where the tools were assessed across representative tasks including component implementation, utility function development, and test creation. The findings indicate that AI-based tools can significantly improve productivity. However, the generated outputs frequently require manual review, correction, and refinement to ensure correctness and alignment with project requirements. Each tool demonstrated distinct strengths, but no single tool consistently outperformed the others across all evaluated tasks. The results suggest that AI tools are most effective when used as supportive assistants rather than autonomous replacements for developers. Future research may extend this evaluation to larger-scale projects, different frameworks, and more complex development scenarios.