This article explores the current status and future trends of AI applications in machine tools and components. AI enhances machining precision, reduces costs, predicts maintenance, and drives smart manufacturing, green production, and customized services. Global and domestic companies have launched AI solutions such as digital twins, edge computing, generative AI, and predictive diagnostics. Looking ahead, AI will accelerate smart factory implementation, industrial IoT integration, and new business models. Companies should strengthen data analytics, collaborate on R&D, develop AI talent, and promote market education to seize opportunities in intelligent manufacturing.

The EU Corporate Sustainability Due Diligence Directive (CSDDD) mandates large companies to conduct human rights and environmental due diligence across global supply chains and develop climate transition plans. Effective in 2024, it must be transposed into national law by 2026, with phased implementation from 2027 to 2029. Non-compliance may incur fines up to 5% of global turnover. Companies must integrate risk management, establish grievance mechanisms, and publish annual reports. Although SMEs are not directly regulated, they will face indirect pressure and should prepare early.

Global manufacturing value chains are being reshaped by geopolitical tensions, climate change, technological advances, and conflicts. Nations are prioritizing resilient supply chains, reducing reliance on single sources, and promoting domestic semiconductor and EV industries through policies and subsidies. The U.S. and Europe are investing heavily in chip production, while China strengthens R&D and dominates the EV value chain. Going forward, supply chain diversification and strategic industry competition will continue to redefine the global economic landscape.

Taiwan’s machine tool industry faces intense global competition and must explore new markets. The semiconductor sector, with its complete supply chain, offers a promising opportunity. Leading international players such as TRUMPF and DMG MORI have advanced in laser and ultrasonic machining technologies, while domestic manufacturers like JunLi, Tongtai, and HIWIN focus on wafer grinding, laser processing, and automation systems. Future strategies should emphasize technology innovation, supply chain integration, and global market expansion to enhance competitiveness and achieve mutual growth.

In 2023, the global machine tool market faced weak demand due to inflation, interest rate hikes, and China’s slower recovery, while geopolitical risks further dampened investment. Global consumption totaled about $79 billion, down 5%. China remained the largest consumer despite a 9.6% decline, while the U.S. grew 8.2%, and Mexico and Turkey showed strong gains. Production slightly decreased overall, with Germany, the U.S., and Spain growing, but China, Japan, and Taiwan declining. Germany, China, and Japan led exports; the U.S. and China topped imports. Future demand will focus on net-zero emissions, smart technologies, and digital and green transformation.

The Southeast Asian EV market is growing rapidly, driven by global decarbonization trends and government policies. By 2035, sales are projected to reach 8.5 million units, with an ecosystem value of $8–12 billion. Thailand and Indonesia are key investment hubs—Thailand attracts foreign manufacturers through incentives, while Indonesia leverages its nickel resources to develop battery supply chains. Chinese players like BYD dominate Thailand’s market, highlighting the importance of localization and policy support. Taiwanese firms entering the region should consider geopolitical risks and learn from Chinese strategies to strengthen their New Southbound initiatives.

The U.S. continues expanding export controls on China, targeting semiconductors, AI, and other critical technologies, while promoting multilateral cooperation to maintain its technological edge. The U.S.-China tech conflict is intensifying, with the EU assessing related risks. China counters by restricting exports of gallium and germanium, but this may drive Western nations to rebuild supply chains. Global electronics supply chains face restructuring, requiring companies to adapt strategies to geopolitical and economic risks

Generative Artificial Intelligence (GenAI) leverages machine learning and deep learning to autonomously create text, images, code, and other content after extensive data training. It offers broad applications in dialogue systems, document generation, translation, code development, decision support, and design. In manufacturing and machinery industries, GenAI can accelerate product design, optimize processes, and enhance robotics control through natural language commands and multimodal integration. Despite its potential, challenges remain, including data bias, accuracy limitations, high development costs, and intellectual property concerns. Taiwan actively promotes localized GenAI models such as TAIDE, Formosa Foundation Model (FFM), and MediaTek DaVinci, alongside initiatives in machine tool applications to improve efficiency and competitiveness. Enterprises adopting GenAI should evaluate value versus risk, establish governance frameworks, and choose suitable implementation strategies—ranging from proprietary model development to fine-tuning or prompt engineering—to maximize benefits while mitigating security and compliance risks.