The “AI Adoption and Future Competitiveness” survey released by the Chung-Hua Institution for Economic Research (CIER) shows that AI adoption is gradually expanding across the manufacturing sector. Some 69% of manufacturers have already adopted AI or are evaluating or planning its adoption. Current applications still focus largely on automating administrative tasks, customer service, document processing, and other workflows. Only a small number of companies have advanced to smart production or fully automated factories. By industry, the transportation equipment sector leads in AI adoption, with the relevant share reaching 88.2%.
AI Applications Start with Process Automation, While Smart Production Requires Further Development
The survey shows that 58.6% of manufacturers use AI to automate administrative tasks, customer service, document processing, and other workflows. This is currently the most common application. Market demand forecasting, sales, and customer management rank second at 40.2%. By comparison, 27.8% use Internet of Things (IoT) and sensor data for equipment and energy consumption monitoring, while 20.1% use AI-powered smart warehousing and logistics. Only 18.3% have deployed AI-powered smart production or unmanned lights-out factories, which represent more advanced forms of smart manufacturing.
Chih-Yen Tai, an Associate Research Fellow at the International Economic Research Division of the CIER, said AI currently serves mainly to improve processes and increase the efficiency of information processing in manufacturing. Most companies begin with applications that have lower adoption barriers and easily measurable benefits. They then gradually expand into IoT integration and smart production. The sector has yet to enter a stage of full automation or large-scale workforce replacement.
Among the 31% of manufacturers that have not adopted AI, 46.1% said they currently have no relevant need. Another 34.2% cited excessive implementation and maintenance costs, while 22.4% said they lacked sufficient understanding of the technology. Tai said the next phase of AI adoption will depend on more than technological advances. Companies must also identify clear use cases, establish cost-benefit models, and strengthen their organizational capacity to implement AI.
Transportation Equipment Industry Leads in AI Adoption, but High Adoption Does Not Mean Full Smart Transformation
By industry, the transportation equipment sector recorded the highest AI adoption rate at 88.2%. The electronics and optical industry ranked second at 72%, followed by the food and textile industry at 69.6%. Adoption rates in the electrical and mechanical equipment, basic materials, and chemical, biotechnology, and healthcare industries were all below 65%.
Even in industries with higher AI adoption rates, applications remain focused on process automation. The transportation equipment industry reported a process automation rate of 73.3% and placed greater emphasis on IoT and sensor data. Process automation accounted for 61.1% of AI applications in the electronics and optical industry, followed by a stronger focus on sales and demand forecasting.
Tai said manufacturers are not adopting AI primarily to achieve immediate cost reductions or cut jobs. Instead, they aim to redesign workflows, reallocate job functions, and improve visibility into returns on investment. Companies should focus on workforce retraining, data governance, process accountability, and identifying use cases that generate tangible benefits.
Non-Manufacturing Industries Accelerate AI Adoption as Cost Savings Gradually Emerge
AI adoption is also accelerating across non-manufacturing industries. Some 60.4% of companies have already adopted AI or are evaluating or planning its adoption. Applications likewise center on administrative tasks, customer service, and document processing. Among companies that have adopted AI, 68.9% use it for AI agents or process automation, while 41.1% apply it to sales, customer management, and demand forecasting.
By comparison, only 17.2% use AI for unmanned services or smart operations. AIoT applications for managing foot traffic, equipment, environmental conditions, or energy consumption account for 13.9%, while smart warehousing or logistics represents just 9.9%. These figures show that AI applications in non-manufacturing industries have yet to expand widely into physical environments or end-to-end automation.
Regarding workforce impacts, 34.4% of companies expect AI to change job responsibilities or lead to the reallocation of job functions. Only 6.8% anticipate a significant decline in labor demand. Another 10.4% expect AI to create new businesses and job functions or increase demand for AI professionals. In terms of cost benefits, 40% of companies expect AI to improve service performance or workflow allocation, while 23.2% believe it could moderately or significantly reduce operating costs.
Tai said non-manufacturing industries are also not using AI primarily to replace workers immediately. Their priority is to improve service processes, customer interactions, and internal operations. As companies gain experience with AI applications, its value will extend beyond isolated efficiency gains to process redesign, workforce transformation, and smart operations. A company’s ability to capitalize on this transformation will be a key determinant of its future competitiveness.
Source: Economic Daily News (August 4, 2026). Will AI Really Replace Workers? How Industries Are Using AI Today. Economic Daily News. https://money.udn.com/money/story/7307/9677311