산업 인공지능의 기술경쟁력과 정책 시사점

다국어 초록 (Multilingual Abstract)

Worldwide competition for securing leadership in Artificial Intelligence(AI) technology, which is considered the key to industrial digital transformation and new growth momentum, is getting intense. However, Korea’s competitiveness in AI technology is found to be generally lagging behind that of major countries, and the fact that the introduction and utilization of AI in the industry and industrial digital transformation are generally sluggish is evidenced through several sources. Even though it is essential to find ways to enhance the technological competitiveness of industrial AI, which is AI with the purpose of use in the manufacturing industry, necessary empirical evidence is extremely insufficient in Korea. The aim of this study is to provide empirical evidence of the current status regarding the development of industrial AI in Korea and the factors affecting the technological competitiveness of industrial AI, thereby providing several policy implications.
First of all, we constructed a dataset consisting of AI patents, which include industrial AI patents, applied between 2007 and 2019 and finally registered (as of July 2022) by linking patent data, government R&D project data, and corporate financial data. Then we using the dataset analyzed the status of industrial AI development, regarding government support, and the determinants of the technological competitiveness of industrial AI and found the following. First, domestic AI technology development and government support are focused on AI for general purposes rather than industrial AI. Second, the Korean government is focusing its support for AI technology development including industrial AI in terms of basic research stage rather than applied research or development stage. Third, it is necessary to expand government R&D support in terms of the development stage in order to enhance the overall competitiveness of industrial AI technology. Fourth, the need for government support centered on the development stage for industrial AI is more pronounced for small and medium enterprises. Finally, it can be effective in enhancing the technological competitiveness of industrial AI to activate technology transactions between firms in manufacturing sector and those in ICT sectors.
This study comprehensively provides information and policy implications on the current status of domestic industrial AI and the determinants of its technological competitiveness by utilizing the advantages of patent data including details and potentials for linking to various sources of data. However, the results of this study depend mainly on patent data, and hence, it can be followed by studies based on comprehensively various other data sources including surveys in the future.

목차 (Table of Contents)

• [표지]
• [머리말]
• [차례]
• 표 차례
• 그림 차례
• [요약]
• [제1장 서론]
• 1. 연구 배경 및 필요성
• 2. 연구의 목적과 구성
• [제2장 산업 인공지능 개요 및 관련 정책 동향]
• 1. 산업 디지털전환과 산업 인공지능
• 2. 국내 산업 디지털전환 및 인공지능 관련 정책
• 3. 소결
• [제3장 산업 인공지능 특허 분석 방법론]
• 1. 연구 자료
• 2. 인공지능 및 산업 인공지능 특허 분류
• 3. 특허 인용 네트워크 분석 방법론
• [제4장 국내 인공지능 및 산업 인공지능 특허 동향]
• 1. 일반 특허 동향
• 2. 정부 R&D 성과 특허 동향
• 3. 소결
• [제5장 산업 인공지능 기술경쟁력 결정요인 실증분석]
• 1. 주요 변수 및 회귀분석 모형
• 2. 실증분석 결과
• 3. 소결
• [제6장 결론]
• 1. 주요 연구 결과 및 정책 시사점
• 2. 본 연구의 기여 및 향후 연구
• [참고문헌]
• [Abstract]