AI Utilization Gap Between Large and Small Enterprises Highlights Structural Challenges

The recent report by the Korea Chamber of Commerce and Industry (KCCI), released on the 11th, emphasizes a growing structural issue regarding the utilization of Generative AI across different enterprise sizes in South Korea. Based on a survey conducted among approximately 3,000 wage workers aged 20 and over, the report reveals that the utilization rate of Generative AI among large enterprises stands at 66.5%, compared to only 52.7% for small and medium-sized enterprises (SMEs), indicating a significant gap of 13.8 percentage points.

However, when factoring in other elements like organizational support frameworks and individual competency in prompt engineering, the gap narrows considerably to just 4 percentage points. This finding suggests that SMEs can potentially harness AI capabilities comparable to those of larger enterprises if supportive organizational conditions are established.

Companies that foster a culture encouraging AI utilization see a notable increase in usage probabilities: a 15.5 percentage point boost occurs when companies actively promote AI adoption. Additionally, offering subsidies for AI subscription fees yields an 8.1 percentage point increase in utilization likelihood. The report also highlights individual factors such as personal competency in prompt engineering (23.5 percentage points) and positive attitudes towards AI (21.4-40.0 percentage points) as key contributors to increased utilization.

The disparity in organizational support is stark, illustrated by the fact that 70.4% of SMEs lack a structured roadmap for adopting Generative AI,far surpassing the 54.4% of larger firms without such a plan. Although both segments exhibit deficiencies in systematic AI strategy development, the void in SMEs is particularly pronounced. Areas where support is lacking for SMEs include education and training (34.7% for large firms vs. 24.9% for SMEs) and the provision of internal guidelines (33.8% for large firms vs. 24.3% for SMEs).

The differentiation in how reduced working hours from AI are utilized also reveals insights into employee behavior between large and small enterprises. While both demographics prioritize using time savings to enhance existing work quality (32.6% for large firms vs. 29.5% for SMEs), their second choices diverge sharply. Employees in large enterprises utilize the time saved for new projects (22.6%), while those in SMEs are more inclined to take personal breaks and secure leisure time (27.3%).

The report underscores a pronounced geographical and sectoral polarization in AI utilization, particularly within the manufacturing sector where the gap reaches an alarming 24.2 percentage points, compared to 9.2 points in service industries. Moreover, SMEs in the capital region report a significantly higher usage rate (57.3%) than those in non-capital regions (47.8%), which positions manufacturing and rural SMEs as critical areas needing strategic support for AI adoption.

To address the disparities between large and small enterprises in AI utilization, the KCCI experts argue for comprehensive responses at both corporate and governmental levels. Recommendations include expanding AI-specialized courses within employment insurance vocational training and launching customized programs aimed specifically at non-capital and manufacturing sectors.

Furthermore, it is essential for SMEs to establish systematic adoption strategies, providing accessibility to diagnostic consultations and standardized roadmaps. Simplifying requirements for subsidies related to AI tools and subscription costs is critical for enhancing access. To ensure that reduced hours do not merely translate to downtime but lead to genuine business advancements, there should be a shift towards performance-linked job redesigns accompanied by incentives for internal knowledge sharing.

The KCCI also highlighted the inclusion of the upcoming ‘Everybody's AI Project’, set to be launched in the second half of this year and aimed at providing a proprietary AI model for free, as a potential catalyst for empowering SMEs to effectively utilize AI in their operations. KCCI Economic Research Institute head, Park Yang-su, remarked, “The gap in AI utilization between large and small firms arises from not just individual attitudes but significantly from organizational policies and supports. It is crucial to design precise systems that enhance the conditions for SMEs to adopt AI and strengthen employee capabilities.”