Despite expectations that artificial intelligence (AI) would serve as a "master key" to drive industrial innovation, findings indicate that its actual application in industrial settings has been slow.
According to an investigation by THE AI on the 10th, enthusiasm for AI in industrial workplaces is waning, and the tangible benefits of adoption remain minimal. In some sites, AI-powered translation tools for communication with foreign workers were the only AI technologies being effectively utilized.
A manager working in a manufacturing facility commented, “There are concerns that AI will replace human workers, but in reality, there are even greater concerns about whether AI can be effectively utilized at all in industrial settings.” He further stated, “AI providers market their technology as a universal solution for any industry, but the reality in the field is quite different.”
73% of Domestic Manufacturers Have Adopted AI? Workers Say They Don’t Feel the Impact
According to the Korea International Trade Association (KITA) on the 10th, 73% of domestic manufacturing companies have either adopted or are in the testing phase for AI technology. Citing the Manufacturing Trends Report by U.S. firm Salesforce, KITA explained, “AI adoption among domestic manufacturers is at approximately 73%, slightly below the global average of 80%.”
These companies aim to use AI to enhance productivity and optimize energy efficiency. Ultimately, their goal is to maximize production with minimal energy consumption, improve cost competitiveness, and ensure workplace safety by preventing accidents and equipment failures.
However, industry professionals tell a different story. Many report that AI implementation remains premature and challenging. A representative from the textile industry stated, “I believe it’s still too early to apply AI technologies. We are testing and discussing various developed technologies, but the process of actual implementation will take a very long time.”
Workers also expressed that they do not feel any tangible benefits from AI adoption, contradicting corporate claims that emphasize AI integration. A professional from the domestic chemical industry noted, “The company announced in a press release that it had adopted AI, but in reality, the only AI-based implementation was sensors to restrict access to hazardous areas like blind spots or restricted zones. However, since these areas are rarely accessed, we don’t really feel the impact of these AI sensors.”
The only AI technology that seemed practically useful was AI-powered translation tools. A professional from the shipbuilding industry mentioned that the recent labor shortage had led to an influx of foreign workers under the E-9 visa program, making AI translation agents the most helpful AI tool. He stated, “More than 80% of newly hired field workers are foreign laborers. Communication with workers from Vietnam, China, and other countries is a major challenge, and in this aspect, AI has been a great help.”
Lack of Data Delays AI Utilization… Master Key or ‘AI Bubble’ in the Making?
One of the main reasons companies struggle to leverage AI is a lack of sufficient data. To establish AI-optimized systems for production lines, extensive data from various industrial processes is required. However, industry professionals report that such data is still insufficient.
A representative from the steel industry explained that AI must be optimized differently for each industrial setting, but the necessary data for such optimization remains lacking. He elaborated, “In the steel industry, for example, there are different categories such as steel pipes, steel plates, and hot-rolled steel, each with different manufacturing processes and factory layouts. AI optimization must be tailored to each specific product and process, but we currently lack the necessary data to achieve this.” He added, “We are in the process of collecting data through testing and gradually optimizing production lines.”
He warned that the current expectation of AI as a universal solution that will revolutionize all industries could ultimately be harmful. “AI companies promote the idea that AI can bring innovation to all fields, but such a perception may lead to an ‘AI bubble’,” he said.
He concluded, “Right now, many are focusing only on a future where AI has been successfully implemented, seeing it as the ultimate solution. However, there are still many challenges to overcome, requiring significant financial and time resources.” He further noted, “The industry’s perspective on AI is quite different from what is often portrayed in the media. We still need much more time.”