A Major Transformation Is Coming to K-Manufacturing... The 'Golden Time' for AI Collaboration Between Large and Small Companies [AI Autonomous Manufacturing Opens the Future]

While Manufacturers Hesitate to Adopt AI, Operating Rates Barely Reach 70%
K-Manufacturing Set for Major Transformation with AI... Breaking On-Site Inertia
Urgent Need for Focused Investment to Counter China’s Shorter Industry Track Record

Editor's Note
The backdrop to South Korea's entry into an era of sub-1% growth rates includes sluggish domestic demand, weak exports, and declining competitiveness in manufacturing. Experts point to artificial intelligence (AI) as the only card capable of overcoming these challenges. There is a prevailing view that AI will play a major role not only in enhancing corporate competitiveness to keep pace with rapidly growing Chinese manufacturers, but also in fostering coexistence between large corporations and small and medium-sized enterprises (SMEs). The key, they argue, is for large companies to leverage their massive infrastructure and investment, while SMEs contribute flexibility and on-site responsiveness, jointly driving open innovation and triggering an industrial ecosystem transformation through AI technology. At the core lies the high-quality tacit knowledge that K-manufacturing has accumulated over more than half a century. The movement to combine AI with data-driven innovation is already underway. Over the course of four articles, we will examine these developments on the ground and explore strategies for building sustainable competitiveness.

Shinsung Delta Tech, a company specializing in OEM and ODM for home appliances, posted consolidated sales of nearly 1 trillion won last year. Recently, the company demonstrated its competitiveness by winning the Innovation Award in the Smart Home category at CES 2025 for its senior care robot, "Remi," which is expected to drive the company's future growth. Kwangwoo, a manufacturer specializing in industrial specialty lubricants, has earned a reputation as an SME that successfully localized synthetic ester products previously dependent on imports. The company's sales, which stood at 25 billion won in 2015, jumped to 50 billion won last year and are expected to reach 70 billion won this year. The defect rate of its products, once around 15%, has recently dropped significantly to the 2-3% range.

Both companies are mid-sized businesses with nearly 40 years of history and share the distinction of having achieved a new leap forward through AI adoption. Shinsung Delta Tech partnered with LG Electronics, while Kwangwoo collaborated with POSCO, achieving results in technology development and productivity improvement. They are exemplary cases of successfully building smart factories or converting certain processes to autonomous manufacturing. While OEM and ODM home appliance and lubricant production facilities moved overseas in search of cheap labor, these companies steadfastly remained and focused on technological advancement.

Manufacturers Hesitant to Adopt AI, Utilization Rate Barely at 70%

However, for most SMEs, adopting AI technology remains a distant dream. According to the "First Smart Manufacturing Innovation Survey" conducted by the Ministry of SMEs and Startups in April, only 18.6% of the approximately 160,000 small and medium-sized manufacturing companies in South Korea with domestic factories had implemented smart factories. This means that fewer than two out of ten companies have adopted such systems.

The main reason companies hesitate to adopt AI is the burden of conversion costs. According to the Ministry, the average cost to build a smart factory is 1.13 billion won, and even for SMEs, it amounts to 750 million won. However, government support is limited to 50 million won for the basic stage and up to 200 million won for the intermediate stage or higher.

While the industry hesitates to make bold investments and foster cooperation between large and small companies, the vitality of domestic manufacturing is rapidly declining. Since 2011, the average operating rate of the manufacturing sector?an indicator of actual output relative to production capacity?has remained below 80%. In both 2023 and last year, it hovered in the 72% range, dropping to a level similar to 2020 (71.1%), when the spread of COVID-19 severely impacted production facility operations.

K-Manufacturing Poised for Transformation with AI... Breaking the Inertia of Skilled Workers

Experts argue that large corporations and small and medium-sized companies must actively collaborate on AI to convert the vast reservoir of tacit knowledge in domestic manufacturing into data. Tacit knowledge refers to expertise accumulated through personal experience that cannot be easily articulated in writing or manuals. Much of the know-how that fueled the strategic growth of manufacturing since the 1960s and propelled South Korea to become an export powerhouse in the 1980s?spanning semiconductors, displays, shipbuilding, and automobiles?remains dormant in tacit form.

Collaboration and datafication through AI between large and small companies are also seen as the only way to counter China's technological rise. While China has achieved results in strengthening its global competitiveness through its "Made in China 2025" strategy, the actual history of industrial advancement since the policy's announcement in 2015 is little more than a decade. The belief is that combining South Korea's more than 50 years of manufacturing advancement with AI will yield a stronger competitive edge.

Jang Junhyeok, professor at Hanyang University's Department of Electronic Engineering, pointed out, "Legacy industries with long histories, such as shipbuilding, steel, and secondary batteries, have been relatively slow to apply AI." He added, "There are high barriers for new technologies to enter, from problem definition to data collection." He continued, "The manufacturing sector is in particularly fierce competition with China, and now is the time to enhance competitiveness through a dual-track approach that combines AI with other industries."