• Title/Summary/Keyword: AI Company

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How Organizations Legitimize AI Led Organizational Change?

  • Gyeung-min Kim;Heesun Kim
    • 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.

Trends and Implications of Venture Capital Investment in the Artificial Intelligence Industry (인공지능(AI) 산업의 VC 투자 동향과 시사점)

  • S.S., Choi;B.R., Joo;S.J., Yeon
    • Electronics and Telecommunications Trends
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    • v.37 no.6
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    • pp.1-10
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    • 2022
  • Artificial intelligence (AI) has rapidly diffused across industries and societies as nations' essential strategic technology. In innovative technology, such as AI, a startup leads to technological innovation and significantly impacts the expansion of relevant industries. Thus, this study examined the trend of AI startup venture capital (VC) investments globally, focusing on ① noteworthy VC investment statuses (the number and size of the investment, company establishment, and corporate collection), ② the characteristics of each key nation's investments, and ③ the characteristics of each submarket's investments. Among the 11 countries, the results showed that Korea ranked near the bottom for absolute quantitative measures, including the number and size of investments, company establishment, and corporate collection. However, Korea has built a foundation of catching up with what AI-leading countries have established, considering Korea's high growth rate in the number and size of investments and a recent mega-round. This study has practical implications in that it determined the AI startup VC investment status of Korea's rival countries, not only G2 (US and China). The results can be used in policy-making. Furthermore, identifying the AI industry's submarkets and analyzing each market's VC investment status could be used to establish strategies for the AI industry and R&D.

How Trust in Human-like AI-based Service on Social Media Will Influence Customer Engagement: Exploratory Research to Develop the Scale of Trust in Human-like AI-based Service

  • Jin Jingchuan;Shali Wu
    • Asia Marketing Journal
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    • v.26 no.2
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    • pp.129-144
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    • 2024
  • This research is on how people's trust in human-like AI-based service will influence customer engagement (CE). This study will discuss the relationship between trust and CE and explore how people's trust in AI affects CE when they lack knowledge of the company/brand. Items from the philosophical study of trust were extracted to build a scale suitable for trust in AI. The scale's reliability was ensured, and six components of trust in AI were merged into three dimensions: trust based on Quality Assurance, Risk-taking, and Corporate Social Responsibility. Trust based on quality assurance and risk-taking is verified to positively impact customer engagement, and the feelings about AI-based service fully mediate between all three dimensions of trust in AI and CE. The new trust scale for human-like AI-based services on social media sheds light on further research. The relationship between trust in AI and CE provides a theoretical basis for subsequent research.

Current Status of Development and Practice of Artificial Intelligence Solutions for Digital Transformation of Fashion Manufacturers (패션 제조 기업의 디지털 트랜스포메이션을 위한 인공지능 솔루션 개발 및 활용 현황)

  • Kim, Ha Youn;Choi, Woojin;Lee, Yuri;Jang, Seyoon
    • 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.

Frequentist and Bayesian Learning Approaches to Artificial Intelligence

  • Jun, Sunghae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.2
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    • pp.111-118
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    • 2016
  • Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

Artificial Intelligence Technology Trends and IBM Watson References in the Medical Field (인공지능 왓슨 기술과 보건의료의 적용)

  • Lee, Kang Yoon;Kim, Junhewk
    • Korean Medical Education Review
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    • v.18 no.2
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    • pp.51-57
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    • 2016
  • This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.

Case Studies for Insurance Service Marketing Using Artificial Intelligence(AI) in the InsurTech Industry. (인슈어테크(InsurTech)산업에서의 인공지능(AI)을 활용한 보험서비스 마케팅사례 연구)

  • Jo, Jae-Wook
    • Journal of Digital Convergence
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    • v.18 no.10
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    • pp.175-180
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    • 2020
  • Through case studies for insurance service marketing using artificial intelligence(AI) in the insurtech industry, it investigated how innovative technologies(artificial intelligence, machine learning etc.) are being used in the insurance ecosystems. In particular, through domestic and international case studies, it was examined by Lemonade's service of insurance contracts and getting the indemnity and AI company's service of calculating the compensation through a medical certificate image based on OCR, which brought disruptive innovations using artificial intelligence. As a result of the case analysis, these services have drastically shortened the lead time of insurance contracts and payment through machine learning using numerous customer data based on artificial intelligence. And accurate and reasonable compensation was calculated in the estimation of indemnity, which has a lot of disputes between customers and insurance companies. It was able to increase customer satisfaction and customer value.

Development of K-Digital Training Digital Leading Company Academy FLYAI Curriculum (K-디지털 트레이닝 디지털 선도기업 아카데미 FLYAI 교육과정 개발)

  • Kim, Hwang;Jung, Hae Keom
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.397-398
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    • 2022
  • 본 논문에서는 SK텔레콤에서 진행하는 디지털 선도기업 아카데미 FLYAI의 교육과정을 설계하고 개발한다. 이 교육과정은 Project Based Learning(272시간)과 Product Based Learning(128시간)으로 구성하여 총 400시간을 교육하도록 설계한다. 특히 Product Based Learning의 AI-Hackathon(80시간)에서는 SK텔레콤 각 부서에서 제안하는 제픔을 기획하고 개발하는 과정으로 SK텔레콤 AI 개발자들이 멘토로 참여함으로써 기업 현장의 경험을 체험할 수 있도록 개발한다.

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Measures to minimize the side effects of the increased use of Artificial Intelligence Robo-Advisor (인공지능 로보어드바이저의 활성화에 따른 부작용 최소화를 위한 제도적 보완점)

  • Kim, Dong Ju;Kwon, Hun Yeong;Lim, Jong In
    • Journal of the Korea Convergence Society
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    • v.8 no.10
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    • pp.67-73
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    • 2017
  • In this study, we mainly inquired into structural reforms of the current legal system that could minimize the side effects and protect financial customers as the use of AI robo-advisor were increasing. First, regarding a specific reform, it is necessary to introduce and establish a rapid detection system for unusual transactions by the Robo-advisor management company, the strict liability of the management company, the management company's mandatory obligation to obtain indemnity insurance, and limited criminal penalties. Furthermore, it is necessary to establish a comprehensive basic law regarding AI. In this basic law, the promotion of the development of AI technology and the minimization of side effects should be dealt with in harmony with each other. Like the approach of this study, we hope that similarly detailed and practical discussions will be made on the AI era from various perspectives in the future.

A Study on the Improvement Plan of AI Voucher Support Project based on the Perception of AI Solution Companies (AI 솔루션 기업 관점의 AI 바우처 지원사업 개선방안 연구)

  • Cho, Ji Yeon;Song, In-Kuk
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.4
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    • pp.149-156
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    • 2022
  • In the recent pandemic situation, importance of artificial intelligence has been highlighted and major countries are making efforts to secure leadership in AI technology. The Korean government has been continuously expanding government investment to secure technological competitiveness. Despite the importance of efficient operation strategies for government-supported projects, related discussions rarely existed. Therefore, this study aims to analyze the AI voucher support project, which is a representative government project in the AI field, and to suggest improvement plans. An interview with AI solution companies was conducted, and issues in the process of promoting AI voucher support projects were identified through content analysis. Based on the analysis results, improvement plans were presented in stages of project preparation, progression, termination, and follow-up management. This study has significance in suggesting improvement plans for the government support project for the successful growth of the AI industry at a time when the importance of AI is increasing.