The technical achievement of AlphaGo marked a pivotal moment in the evolution of artificial intelligence, accelerating the momentum of the Fourth Industrial Revolution. In response, leading nations have crafted AI policies tailored to their specific national contexts and strategic goals. Yet beyond technological advancement and policy design lies a fundamental question: how should humans coexist with AI? This presentation approaches the question through the lens of the manufacturing industry—one of the sectors most deeply impacted by AI adoption. It will outline the key trajectories of recent developments, examine future challenges, and introduce real-world case studies that reveal a crucial insight: domain expertise and tacit knowledge remain indispensable in bridging the gap between AI capabilities and practical implementation. These cases, drawn from real industrial scenarios, suggest that the final stretch in realizing AI’s full potential relies not just on algorithms or data, but on people who understand both the technology and the domain it is applied to. As Professor Andrew Ng has aptly stated, “Those who can use AI will replace those who cannot.” In a time of rapid change, no one remains on the sidelines. The ability to understand, adapt to, and work with AI is becoming a defining skill for the next generation of professionals and researchers.

Shang-Chih Lin is an assistant professor of automatic control engineering at Feng Chia University, Taiwan. He obtained a Ph.D. from the electrical engineering at National Taiwan University of Science and Technology, Taiwan. His research work spansartificial intelligence, big data analysis, smart manufacturing, and unmanned vehicles. He has worked at Academia Sinica (Research Center for Information Technology Innovation & Institute of Information Science) and Yeong Chin Machinery Industries Co., Ltd. His research work has also won several awards, including the Ph.D. dissertation award from TFSA, the extraordinary servicemen award from MOI, and the Best Paper Award (CACS 2024&2022, ITAOI 2024, ISME 2023, ISQM 2018, IEEE ICAM 2018, EPE 2016, ICSSE 2016, and ICENS 2015). He is also a reviewer for some well-known journals, including IEEE TII, IEEE Access, IEEE/CAA JAS, JIM, IJFS, JCIE, JVET, AME.