Design and Implementation of Generative AI-Based Script-to-Video Automation with YouTube Integration

Abstract The rapid expansion of digital media usage has increased the demand for more effective and scalable approaches to video generation. Traditional video creation involves substantial manual effort, significant time consumption, and specialized technical expertise, making it difficult for individuals and small organizations to produce consistent, high-quality content. With the advancement of Generative Artificial Intelligence (AI), automated video production has become feasible through modern techniques in text, image, audio, and video synthesis. This paper presents an overview of Generative AI–based script-to-video automation systems combined with YouTube publishing capabilities. The proposed approach focuses on transforming textual scripts into complete videos using Natural Language Processing (NLP), text-to-speech conversion, AI-generated visuals, automated background audio integration, and video composition methods. Additionally, YouTube Data APIs are utilized to automate video uploading, metadata creation, scheduling, and performance tracking. The proposed system architecture highlights the integration of multiple AI services and automation tools to enable complete end-to-end content generation with minimal human involvement. Such solutions can help reduce production expenses, maintain content consistency, and support large-scale video creation. This study emphasizes the growing relevance of AI-driven video automation for content creators, educators, marketers, and the digital media sector