The fast development of Generative AI has transformed the content production process, providing machines with the capabilities to produce media of high quality and semantic integrity. Among the most challenging uses of this technology, one can opt for creating a video based on complicated textual data. This paper compares three prominent Generative AI tools—Sora (OpenAI), Runway Gen-3, and Pika Labs—and assesses their capabilities in converting narrative scripts into videos. The study delves into multi-modal representation learning, text encoding, video processing techniques, and transformer-based generative models. The dataset includes diverse scripts from various genres, enabling an in-depth analysis of video generation performance. Both automated metrics (CLIPscore) and human-assessed criteria, including visual coherence, quality, and emotional alignment, are employed to evaluate these tools. The paper also discusses the uses of this technology in various industries and the opportunities and threats that accompany the technology. This study can present some valuable insights into the transformative potential of video creation through AI-driven processes based on experimental outputs.