Small and midsize businesses' use of Generative AI lags far behind large companies, but an analysis found that when conditions such as company support are the same as at large companies, the usage gap is not large. It argued that creating the right conditions is urgent to bridge the AI usage gap between large companies and small and midsize businesses.
On the 10th, the Korea Chamber of Commerce and Industry Economic Research Institute said in its report, "The gap in Generative AI use between large and small firms: the role of capability and organizational environment," that the simple Generative AI usage rate gap between large companies and small and midsize businesses was 13.8 percentage points. It said 66.5% of large companies and 52.7% of small and midsize businesses are using Generative AI. The findings are based on a survey of about 3,000 wage workers nationwide aged 20 or older.
However, when other factors, including company support systems and workers' prompt engineering capability, were included in the analysis, the pure usage gap attributable to company size itself narrowed to 4 percentage points. The report said, "Even small and midsize businesses can use AI as well as large companies if the organization creates an environment for use," which suggests this.
In particular, when a company actively encourages in-house AI use, workers' AI usage was 15.5 percentage points higher than at corporations that do not. Even when the company provided subsidies such as for subscription fees, the usage rate rose by 8.1 percentage points. Workers' individual prompt engineering capability (23.5 percentage points) and acceptance attitude (21.4–40.0 percentage points) were also major factors that increased usage. Prompt engineering is the design of questions and instructions given to AI.
These differences in support environments show up clearly in the reality of small and midsize businesses' weak AI support infrastructure. A survey of corporations' Generative AI policies and work environments found that 70.4% of small and midsize businesses do not have a Generative AI adoption roadmap. This is 16 percentage points higher than the 54.4% of large companies, indicating a large gap in systematic AI strategy among small and midsize businesses.
In addition, in most company support items—such as education and training (34.7% for large companies, 24.9% for small and midsize businesses), provision of internal guidelines and manuals (33.8% for large companies, 24.3% for small and midsize businesses), and provision of in-house developed or customized AI tools (11.4% for large companies, 5.7% for small and midsize businesses)—small and midsize businesses significantly lagged large companies.
How time saved with Generative AI is used also differed between large companies and small and midsize businesses. Workers at both large companies and small and midsize businesses chose "investing in improving the quality of existing work" as their top priority for time saved by AI. However, for the second priority, large-company workers chose "carrying out new projects and tasks (22.6%)," while small and midsize business workers selected "rest and securing personal time outside of work (27.3%)."
Research fellow Kim Yong-mi said, "We observe a difference between large and small firms in how time saved by Generative AI is reinvested to create new added value," and added, "Further research is needed, but this suggests that the short-term AI usage gap could accumulate into a productivity gap in the mid to long term."
Polarization by industry and region was also evident. The usage gap between large and small firms in services was 9.2 percentage points, while the gap in manufacturing reached 24.2 percentage points, or 2.6 times as large. Looking at small and midsize business usage by region, the Seoul metropolitan area (57.3%) far outpaced non-metropolitan areas (47.8%).
KORCHAM's Economic Research Institute stressed that a comprehensive response by corporations and the government is needed to bridge the Generative AI usage gap between large companies and small and midsize businesses. It recommended expanding AI-specialized courses within employment insurance vocational training to strengthen worker capabilities, and pursuing tailored programs for blind spots such as non-metropolitan regions and manufacturing. It said diagnostics and consulting, along with a standard roadmap, should be distributed to help small and midsize businesses establish systematic adoption strategies, and that requirements for supporting AI subscription fees and tool adoption expense should be simplified to improve access.