• Journal of the Korea Society of Computer and Information
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• v.29 no.11
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• pp.353-369
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• 2024

This paper presents strategies for enhancing productivity and strengthening global competitiveness as the domestic shipbuilding industry transitions into the era of Artificial Intelligence Transformation (AX), moving beyond digital transformation. Historically a labor-intensive industry, shipbuilding has evolved into smart shipyards powered by automation and digitalization, with increasing emphasis on green regulations and the importance of green fuels. The urgent adoption of alternative fuels, such as ammonia and liquid hydrogen, is critical in this context. However, the industry faces new challenges amid intensifying global competition and rapid technological changes. This study analyzes both domestic and international cases of AI transformation and the adoption of eco-friendly fuels in shipbuilding companies, proposing ways to manage risks through the establishment of AI governance to ensure sustainable growth. In particular, by utilizing the backcasting method, the study sets short-term, mid-term, and long-term goals while deriving phased strategies to provide significant insights and implications for policy formulation and corporate strategies aimed at the AI transformation of the domestic shipbuilding industry while complying with environmental regulations.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.302-309
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• 2023

Artificial intelligence (AI) plays a crucial role in the intelligent development of China's power system. It is also an important part of the digital development of the power grid. The development of AI determines whether the digital transformation of China's power system can be successfully implemented. Therefore, this paper discusses the digital transformation of the power grid based on AI technologies. The author has established a digital evaluation index system to reflect the development of the power grid in one province. Both qualitative and quantitative methods have been adopted in the analysis, which delves into the economic effectiveness, quality, and coordination of power grid development in the province in a comprehensive way. Results show that, to meet the needs of the power grid's digital transformation, the correlation coefficient between the power grid's development and the province's overall coordination has been increasing in recent years.

• Asia pacific journal of information systems
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• v.32 no.3
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• pp.461-476
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• 2022

AI is recognized to be a key technology for digital transformation (DT) and the value of AI is considered to determine the future of the company. However, in reality, although managers acknowledge the future value of AI and have plans to introduce it, most are not sure what to expect from AI or how to apply it to their business. This study compares two company cases to demonstrate how an organization has successfully achieved AI led organizational change while another failed. Specifically, by taking institutionalist's view, this study examines how the legitimacy enables and constrains AI led organizational changes in organization's practices, processes, and infrastructure. The results of this study indicate that for the success of AI led organizational changes, the legitimacy plays an important role by reducing the challenges from stakeholders and increasing the institutional momentum to move through the phases of the change.

• Journal of Fashion Business
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• v.26 no.2
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• pp.28-47
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• 2022

Rapid development of information and communication technology is leading the digital transformation (hereinafter, DT) of various industries. At this point in rapid online transition, fashion manufacturers operating offline-oriented businesses have become highly interested in DT and artificial intelligence (hereinafter AI), which leads DT. The purpose of this study is to examine the development status and application case of AI-based digital technology developed for the fashion industry, and to examine the DT stage and AI application status of domestic fashion manufacturers. Hence, in-depth interviews were conducted with five domestic IT companies developing AI technology for the fashion industry and six domestic fashion manufacturers applying AI technology. After analyzing interviews, study results were as follows: The seven major AI technologies leading the DT of the fashion industry were fashion image recognition, trend analysis, prediction & visualization, automated fashion design generation, demand forecast & optimizing inventory, optimizing logistics, curation, and ad-tech. It was found that domestic fashion manufacturers were striving for innovative changes through DT although the DT stage varied from company to company. This study is of academic significance as it organized technologies specialized in fashion business by analyzing AI-based digitization element technologies that lead DT in the fashion industry. It is also expected to serve as basic study when DT and AI technology development are applied to the fashion field so that traditional domestic fashion manufacturers showing low growth can rise again.

• Journal of Engineering Education Research
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• v.25 no.5
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• pp.44-54
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• 2022

The purpose of this study is to effectively implement the artificial intelligence education required in the digital transformation era. As we enter the era of the 4th industrial revolution, the demand for a great digital transformation in industry is essential, and the nurturing of manpower is presented as an indispensable relationship in the industrial field based on it. The integration of various new technologies that have emerged from the era of the 4th industrial revolution has the greatest purpose in realizing artificial intelligence technology. As the importance of digital competency in the top curriculum reorganization has been highlighted, artificial intelligence education is necessary even in the curriculum reorganization in 2022, and there is a demand in the educational field that it should be converted into a mandatory education in middle and high schools. Artificial intelligence education according to the demands of the times is to develop an artificial intelligence curriculum in universities by reestablishing systematic artificial intelligence education in universities, setting educational goals, and presenting the goals of artificial intelligence education by major. The main direction of this study is to present the relationship between artificial intelligence and each major in university education, develop a curriculum based on artificial intelligence for each major, and link artificial intelligence software for AI education customized for each major. We would like to present a process that can measure the learning outcomes of AI education.

• Convergence Security Journal
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• v.21 no.4
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• pp.3-13
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• 2021

As new technologies such as artificial intelligence (AI), cloud, Internet of Things (IoT), big data, and mobile become organically integrated, a new era of digital transformation is emerging. As a result of this digital transformation, cybersecurity issues have surfaced as a negative side effect. Cyberspace, unlike physical space, has no clear limits, which leads to additional side effects and hazards. While promoting digital transformation in defense, conventional customs and behavioral approaches make it difficult to alter the cybersecurity strategy, even if it is vital to comprehend and prepare the attributes associated with time and technology trends. As a result, in this study, we will look at the direction of technology application in the defense as a result of digital transformation and analyze how to correlate from the standpoint of cybersecurity.

• Journal of Korean Society for Quality Management
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• v.52 no.3
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• pp.557-574
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• 2024

Purpose: This study investigates whether adoption of AI-based systems and technologies improve operational efficiency in healthcare organizations through a systematic review of the literature and real-world examples. Methods: In this study, we divided the AI application cases into care services and administrative functions, then we explored opportunities and challenges in each area. Results: The analysis results indicate that the care service field primarily uses AI-based systems and technologies for quick disease diagnosis and treatment, surgery and disease prediction, and the provision of personalized healthcare services. In the administrative field, AI-based systems and technologies are used to streamline processes and automate tasks for the following functions: patient monitoring through virtual care support systems; automating patient management systems for appointment times, reservations, changes, and no-shows; facilitating patient-medical staff interaction and feedback through interaction support systems; and managing admission and discharge procedures. Conclusion: The results of this study provide valuable insights and significant implications about the application of AI-based systems or technologies for various innovation opportunities in healthcare organizations. As digital transformation accelerates across all industries, these findings provide valuable information to managers of hospitals that are interested in AI adoption, as well as for policymakers involved in the formulation of medical regulations and laws.

• Smart Media Journal
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• v.10 no.1
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• pp.99-107
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• 2021

In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.403-404
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• 2023

In an era where everything is digitalized using AI(Artificial Intelligence), such as the ChatGPT craze, the evacuation guidance system still uses an analog and fixed method, so there is a limit to quick response in case of fire. In order to overcome this, we introduce a digitally transformed evacuation guidance system using AI and discuss its effectiveness.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.054-074
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• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.