특허 포트폴리오 분석을 통한 생성형 AI 기술의 투자 우선순위 도출 방법론 연구
Deriving Investment Priorities for Generative AI Technologies through Patent Portfolio Analysis

초록

This study seeks to identify strategic investment priorities in generative AI field by categorizing key subcategories and analyzing patent positioning of leading countries. Leveraging a large language model (LLM), generative AI patents were classified into nine distinct categories. For each country, technology importance and technology attractiveness indices were computed, and the results were visualized using Ernst's patent portfolio analysis framework. Countries were then positioned into “Invest,” “Selective Investment,” and “Disinvestment” quadrants and corresponding investment strategies were proposed. The analysis revealed that while the United States maintains a leading position across most technology domains, countries such as Korea and China are positioned in quadrants where focused investments are required. This study offers a systematic framework for guiding investment decisions in generative AI technologies and highlights the feasibility of LLM-based patent classification as a tool for strategic patent management.

키워드

Generative AIPatentsPatent portfolio analysisInvestment priorityLarge language model
제목
특허 포트폴리오 분석을 통한 생성형 AI 기술의 투자 우선순위 도출 방법론 연구
제목 (타언어)
Deriving Investment Priorities for Generative AI Technologies through Patent Portfolio Analysis
저자
박철현송지훈
발행일
2025-08
유형
Y
저널명
한국산업융합학회논문집
28
4
페이지
967 ~ 977