According to the report titled "The Gap in Generative AI Utilization Between Large and Small Enterprises: The Role of Capabilities and Organizational Environment" (by Kim Yong-mi and Lee Chang-geun), the gap in basic generative AI utilization rates between large and small enterprises stands at 13.8 percentage points, with large firms at 66.5% and small firms at 52.7%. The study was based on a survey of approximately 3,000 wage workers aged 20 and older nationwide.
While the gap in generative AI utilization is 13.8 percentage points, the report indicates that if companies foster an organizational environment conducive to AI use, small enterprises could achieve levels comparable to large firms. When analyzing factors such as company support systems and employees' prompt engineering skills, the pure utilization gap attributable to company size shrinks significantly to about 4 percentage points.
Samsung recently announced its official adoption of generative AI across all its subsidiaries, initiating a comprehensive transformation of its work processes and corporate culture to be AI-centered, termed "AI Transformation (AX)." Other major companies, including LG Electronics, SK Hynix, Hyundai Motor Group, and Hanwha, are also accelerating automation efforts through the implementation of in-house chatbots and AI support systems.
The report also found that when companies create an environment that encourages AI use, the likelihood of employees utilizing AI increases by 15.5 percentage points compared to those in companies that do not foster such an atmosphere. Additionally, when companies provide subsidies for subscription fees, the utilization probability rises by 8.1 percentage points.
The state of AI support infrastructure reveals that small enterprises significantly lag behind large firms. The report found that 70.4% of small businesses do not have a roadmap for adopting generative AI, compared to 54.4% of large companies. Furthermore, in areas such as training and education (34.7% for large firms vs. 24.9% for small firms), providing internal guidelines and manuals (33.8% for large firms vs. 24.3% for small firms), and offering custom AI tools (11.4% for large firms vs. 5.7% for small firms), small enterprises are falling behind.
An employee from a small business, referred to as A, stated, "While the company encourages the use of generative AI, it only covers 50% of the subscription fee, which is a significant burden. We need more substantial support, such as increased subsidy coverage and educational programs, rather than just encouragement to use it."
The ways in which time saved through generative AI is utilized also show a clear distinction between large and small enterprises. Both large and small enterprise workers ranked investing saved time in improving the quality of existing work as their top priority. However, while employees at large firms used saved time for "new projects and tasks" (22.6%), those at small firms opted for "rest and personal time" (27.3%).
The report also highlighted polarization by industry and region, indicating that the manufacturing sector and small businesses outside the capital region are particularly underserved in AI utilization. The gap in utilization rates between large and small enterprises in the service sector is 9.2 percentage points, while in manufacturing, it reaches 24.2 percentage points, a 2.6-fold difference. Additionally, small businesses in the capital region have a utilization rate of 57.3%, significantly higher than the 47.8% in non-capital regions.
Perceptions regarding AI utilization experiences also emerged as a concern. The primary reason employees hesitate to share their experiences with AI in the workplace is the fear of negative perceptions surrounding generative AI (39.0% for large firms and 33.6% for small firms). This suggests that fostering an open organizational culture alongside AI adoption is essential.
The Korea Chamber of Commerce and Industry's Economic Research Institute emphasized the need for enhancing employee AI capabilities and providing tailored support for small enterprises to bridge the generative AI utilization gap. Recommendations include expanding AI-specific vocational training, offering customized education for non-capital region and manufacturing sectors, providing consulting on adoption strategies and standard roadmaps, and simplifying requirements for AI tool cost support. It is also crucial to redesign job roles and establish incentive systems for sharing internal know-how to ensure that time saved through AI translates into actual productivity gains and business advancement.
Park Yang-soo, head of the Economic Research Institute, stated, "The AI gap between large and small enterprises stems from organizational environments, including company policies and support, beyond individual attitudes. A sophisticated institutional design that encompasses the creation of conditions for small businesses to adopt AI and enhance employee capabilities is vital."
* This article has been translated by AI.
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