<![CDATA[The rapid advancement of artificial intelligence (AI) in recent years has unlocked new opportunities across various fields, including creative industries such as animation. This study focuses on the application and use of generative AI, particularly text-to-image, text-to-video, and image-to-video models, in the process of creating animated scenes. This technology enables the generation of complex and imaginative visual content based solely on narrative descriptions (prompts) provided by users. By automating the production of images or videos, generative AI not only accelerates the production process and significantly reduces costs but also opens doors to exploring more diverse and innovative visual styles. This research analyzes several cutting-edge generative AI technologies, while evaluating their advantages and challenges in producing animated content. The AI-based animation development process is examined using the Multimedia Development Life Cycle (MDLC) framework, which consists of six key stages: Concept, Design, Material Collection, Development, Testing, and Distribution. The findings suggest that generative AI holds great potential for enhancing animators' efficiency, particularly in pre-production stages such as storyboarding, concept art creation, and rough animation. However, while AI can automate many technical aspects, human intervention remains essential to ensure visual consistency, artistic quality, and narrative coherence. Key challenges include dependence on dataset quality, risks of visual style plagiarism, and the need for manual refinement to align outputs with creative visions. Thus, the integration of generative AI in animation production should be viewed as an assistive tool rather than a complete replacement for human creativity. This study provides insights into how AI technology can be optimally utilized in the animation industry while preserving artistic value and originality.]]>
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