The integration of artificial intelligence (AI) into web development is reshaping the design, implementation, and deployment of modern web applications. Rather than being limited to isolated coding tools, AI increasingly supports the entire development lifecycle, including user interface generation, backend service construction, automated testing, security analysis, and continuous deployment. In parallel, modern web systems are evolving toward distributed architectures spanning cloud platforms, edge environments, and client-side execution within browsers. This chapter presents a comprehensive architectural perspective on AI-enabled modern web applications by examining how AI technologies are positioned across development stages and computational layers. A conceptual classification framework is introduced to systematically categorize AI-supported web development approaches based on lifecycle phase, architectural layer, and integration strategy. Building on this framework, an end-to-end AI-driven web development pipeline is proposed, illustrating how human–AI collaboration can support iterative and scalable development processes. In addition, a qualitative comparison between traditional web development practices and AI-enabled approaches is provided, highlighting differences in automation potential, development efficiency, security integration, and architectural flexibility. The analysis shows that AI serves as an augmentation layer rather than a replacement for developers, enhancing productivity while maintaining human oversight in critical design decisions. Overall, the chapter offers a structured and technology-agnostic foundation for understanding emerging AI-native web systems and their architectural implications.