GENERATIVE AI-DRIVEN WEB DEVELOPMENT: A COMPREHENSIVE SYSTEMATIC REVIEW AND FUTURE RESEARCH DIRECTIONS

The rapid advancement of generative artificial intelligence is reshaping the field of web development, opening new possibilities for automated code generation and intelligent interface design. This study employs the PRISMA methodology to conduct a systematic review, analyzing AI-assisted web development research's current state and future directions. Based on an analysis of 46 peer-reviewed studies published between 2020 and 2025, the findings reveal a remarkable growth trend, with an average annual increase of approximately 80%. The research primarily focuses on five core domains: (i) automated code generation, (ii) AI-assisted UI/UX design, (iii) intelligent web optimization, (iv) natural language interfaces, and (v) AI-supported testing. Key challenges identified include the lack of standardized evaluation frameworks, concerns over security and privacy, and limitations in scalability. Accordingly, the study proposes a structured research agenda emphasizing three strategic priorities: developing standardized evaluation metrics for AI-generated interfaces; establishing security protocols integrated into CI/CD pipelines; and advancing distributed inference architectures for efficient deployment on edge computing platforms. Keywords: Artificial intelligence; web development; code generation; large language models; generative AI