Until the mid-20th century, tangible assets were the primary drivers of economic growth. However, with the rise of digital transformation and the Fourth Industrial Revolution, the role of intangible assets has grown significantly in the 21st century. Traditional forms of intangible assets—such as software, R&D, branding, intellectual property rights, design, and organizational capital—have become central to enhancing firm-level and macroeconomic competitiveness. More recently, advanced technologies such as artificial intelligence (AI), big data, and cloud computing are emerging as new forms of intangible capital that contribute to innovation, productivity, and growth. Against this backdrop, this report analyzes the role of intangible asset investment in both major economies and Korea, and provides policy insights by examining its relationship with key economic indicators such as growth, productivity, and firm performance.

This study is composed of four chapters, excluding the introduction and conclusion. Chapter 2 investigates the relationship between intangible asset investment and economic growth using EKIP data. The analysis confirms a positive correlation between intangible investment and productivity growth, although the strength of this relationship varies considerably across countries and industries. Growth accounting results show that while the contribution of tangible assets to growth is declining, the contribution of intangible assets is on the rise—particularly for those included in national accounts. A regression analysis further reveals that economies with higher concentration of intangible asset investment tend to experience stronger medium-term growth. Additionally, the impact of intangible investment appears to vary depending on the economic size of each country group.

Chapter 3 employs a macroeconomic model with optimal intangible asset investment by agents, calibrated separately to Korean and U.S. data. The results show that the distribution of intangible assets is less dispersed in Korea than in the U.S. Model simulations suggest that increasing intangible asset investment—driven by supportive policy—can lead Korea toward a pattern seen in the U.S., where larger firms expand employment and productivity rises. However, this transformation is also accompanied by a deterioration in income distribution, highlighting the trade-offs involved.

Chapter 4 analyzes the relationship between intangible assets and firm performance using data from the Korean Survey of Business Activities between 2006 and 2021. While the proportion of firms holding intangible assets and their total value have increased steadily, the ratio of intangible to total assets has declined since the mid-2010s. Regression results show that greater intangible asset holdings are associated with improvements in sales, labor productivity, and export performance, both in the short term (1 year) and medium to long term (5 years). The positive effects on sales and productivity are particularly persistent. While the impact on export value weakens over time, intangible assets consistently enhance a firm's likelihood of participating in export activities.

Chapter 5 examines the short-term effects of AI exposure on industries in Korea and the U.S. based on data from 2019 to 2022—prior to the widespread adoption of generative AI. In Korea, AI exposure is positively correlated with some employment indicators, but these correlations are not statistically significant once labor productivity is controlled for. Moreover, AI exposure shows a negative relationship with per capita sales and labor share, indicating that technology adoption does not affect all outcomes equally. In contrast, in the U.S., AI exposure is significantly and positively associated with employment, hourly wages, and labor compensation, suggesting that AI adoption may enhance employment and earnings even in the absence of direct productivity gains.

Based on these findings, the report presents several policy implications. First, given the increasing economic contribution of intangible assets, governments should strengthen tax incentives and public support for R&D, software development, and organizational capital—especially in manufacturing and ICT industries—while promoting digitalization in the financial sector. Second, to address the gap in intangible asset accumulation between large firms and SMEs, policies such as easing credit constraints, expanding tax benefits, and providing innovation vouchers for SMEs are needed. At the same time, expanded investment in intangible assets calls for stronger policies on worker retraining to mitigate income polarization. Third, given the demonstrated benefits of intangible assets for firm performance, it is essential to improve access to finance for SMEs through the development of intangible asset–backed lending and to establish policy frameworks for valuing new types of assets such as AI- and big data–driven technologies. Lastly, since the employment and wage effects of AI adoption differ across countries, Korea should focus on strengthening AI-related job training for existing workers, supporting the adoption of AI by SMEs and traditional industries, and implementing labor protection policies for AI-affected sectors.

국문요약

제1장 서론
1. 연구의 배경과 목적
2. 연구의 내용과 구성

제2장 주요국의 무형자산 투자와 경제성장
1. 도입
2. 주요국의 무형자산 투자
3. 무형자산 투자가 포함된 성장회계
4. 무형자산과 경제성장에 대한 회귀분석
5. 소결

제3장 한국의 무형자산 투자가 생산성과 기업 분포에 미치는 영향
1. 도입
2. 선행연구
3. 모형 경제
4. 모수 설정 및 모형 평가
5. 무형자산 투자가 생산성, 기업 크기 분포, 소득 분포에 미치는 영향
6. 소결

제4장 한국기업의 무형자산 보유 현황과 무형자산이 기업 성과에 미치는 영향 분석
1. 도입
2. 한국기업의 무형자산 보유 현황
3. 무형자산과 기업 성과의 관계 분석
4. 소결

제5장 산업별 AI와 경제적 영향
1. 도입
2. 선행연구
3. 한국과 미국의 AI 노출지수
4. 산업별 AI 노출지수 분석 결과
5. 소결

제6장 결론 및 정책 시사점
1. 주요 연구 결과 요약
2. 정책적 시사점

참고문헌

부록
1. 미국
2. 한국

Executive Summary