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This study analyzes the production process of the movie <SAND> produced using generative AI technology to examine the new possibilities and limitations of AI-based movie production, and presents a systematic methodology for prompt design. Unlike conventional movie production that follows a linear process, AI movie production shows an iterative process that breaks down the boundaries between the pre-production, production, and post-production stages. Using various AI tools such as ChatGPT, Midjourney, and Luma, we identify the importance of prompt design and develop customized strategies tailored to the unique characteristics of each tool. The results of the study suggest that although current AI technology has limitations in maintaining narrative consistency and achieving comprehensive storytelling quality, recent technological advancements are rapidly overcoming these limitations. This study is significant in that it contributes to this field by presenting an AI methodology through an AI movie production case, establishing a systematic framework for prompt design, and providing insight into the innovative potential of AI technology in future movie production.

A hierarchical 5G V2X framework is presented to facilitate secure communication between autonomous shuttles and VRU(vulnerable road users), with emphasis on system-level coordination among terminals, vehicles, and networks. In particular, the interconnection structure between MEC(Multi-access Edge Computing) and VRU application servers is the basis for efficiently applying network function virtualization technology, and includes API integration and trust-based access control mechanisms. The orchestration function is modularized and applicable within the VRU application server, and is implemented as a structure that can adapt to dynamic network environments. Network efficiency and safety are built by utilizing the PC5 and Uu interface-based roaming architecture and UDM(Unified Data Management), PCF(Policy Control Functions) functions. This study presents a technical framework for designing a V2X-based road vulnerable protection system, and can contribute to securing real-time communication stability and autonomous driving safety in cities.

AI technology is evaluated as a core technology leading the digital transformation of industry. At the same time, social demands for responsible AI and AI governance that emphasize ethical use of data and transparency of algorithms are also continuously expanding. Accordingly, this study defined the concept of AI governance through a review of prior research, and conducted a case study from a historical perspective to examine the interrelationship between AI governance and non-financial value of a company, such as social reputation. In order to diagnose the AI governance of a company, the AI policy of the company, that is, the terms of use and data processing policy of a generative AI platform company, was used as surrogates, and text mining was used to analyze the AI policy of each platform over time to examine the relationship between the company's reputation and AI governance. As a result, while governance research has traditionally focused on building a system for an organization that manages and supervises managers as agents from the perspective of shareholders, AI governance can be defined as a AI policy management system of a company that manages the reputation of a company by reflecting the demands of various stakeholders in AI policies for responsible AI development and distribution. The establishment of governance that accommodates stakeholders’ demands for the development and distribution of responsible AI can be a goal that companies must achieve in terms of non-financial value, as it secures transparency in innovative creations such as AI, builds trust with stakeholders, and enhances their reputation as a ‘responsible AI provider.’

This study explores the characteristics and implications of AI-generated films by analyzing award-winning works from major domestic and international AI film festivals. By examining how generative AI technologies are applied throughout the filmmaking process—from narrative construction to audiovisual expression and emotional performance—this research reveals the paradigm shift that AI introduces into traditional cinematic conventions. Films such as Story, Total Pixel Space, Lullaby, and The Last Alliance demonstrate how AI functions not only as a technical tool but also as a creative agent capable of shaping narrative logic, aesthetic style, and emotional resonance. Furthermore, these works raise philosophical and ethical questions regarding authorship, emotional authenticity, and legal responsibility. The findings suggest that AI cinema redefines the boundaries of artistic creation by challenging anthropocentric notions of authorship and by fostering a new model of collaborative imagination between human and machine. This study offers a humanities-based perspective on how AI films transform the structures of media production and cultural meaning in the age of artificial intelligence.