A New Era of Software-Defined Innovation
Global demand for semiconductors and advanced computing continues to rise. However, the industry now faces complex challenges linked to software-defined transformation, AI-driven workloads, sustainability pressures, and supply chain diversification. Moreover, companies in industrial automation increasingly rely on powerful control systems, PLC platforms, and factory automation architectures that depend on reliable semiconductor performance. This trend reinforces the strategic importance of next-generation design tools.
Deep Industry Shift Toward Software-Defined Systems
During ICCAD 2025, Ling Lin—Vice President of Siemens EDA and General Manager for China—addressed these issues in her keynote titled “Are We Ready? Using AI to Reconstruct the World and Define the Future Through Software.” She emphasized that modern industries, including automotive and industrial automation, are migrating toward software-defined architectures. For example, the CEO of Mercedes-Benz recently stated that the company is transforming into a software enterprise. Therefore, hardware and software must evolve together to support complex automation ecosystems.
Core Challenges in Semiconductor Development
Ling Lin highlighted three structural challenges: exploding demand, rising costs, and declining project success rates. Adoption of generative AI already exceeds 60 percent, and the rapid expansion of AI workloads drives unprecedented computing needs. In addition, sustainability requirements intensify, as U.S. AI-related electricity consumption may rise from 2 percent to over 12 percent within ten years. Semiconductor supply chains also remain fragile, requiring greater resilience for industries that depend on PLC, DCS, and high-performance control components.
Escalating R&D Costs and Falling First-Pass Success Rates
The semiconductor sector faces significant cost escalation. Development at 16/14 nm required about $90 million, while 7 nm pushed this figure to $250 million. At 3 nm, the R&D investment approaches $540 million. As a result, more than 75 percent of chip projects experience delivery delays, and first-pass yield continues to decline. These indicators show that traditional design methods cannot keep pace with today’s AI-driven automation and control requirements.
From Strong Demand to Accelerating Demand Growth
According to Ling Lin, 2022 marked a turning point in global semiconductor consumption. The market is shifting from strong demand to accelerating demand. Industry forecasts suggest that the semiconductor market may exceed $1.2 trillion by 2030. Moreover, the path from a $1 trillion to a $2 trillion industry will not merely increase competition; it will introduce systemic challenges that require new methodologies and collaborative design models. Therefore, companies must adopt AI-assisted design, digital twins, and integrated automation workflows to remain competitive.
Author’s Insight: AI-Driven Design Will Redefine Industrial Automation
In my experience working with industrial automation projects, the convergence of semiconductor design and automation requirements has never been more visible. Automation platforms now rely on chips optimized for deterministic control, cybersecurity, low-latency communication, and energy-efficient computation. As a result, AI-enabled EDA tools will likely define the next generation of PLC processors, industrial controllers, and embedded DCS modules. Companies that embrace software-accelerated design workflows will gain an advantage in reliability, time-to-market, and lifecycle performance.
Application Scenarios and Solution Use Cases
- Software-Defined Factories: AI-optimized chips for real-time PLC and machine control.
- Automotive Electronics: Advanced SoCs supporting autonomous driving and high-density sensor fusion.
- Edge Industrial Computing: Low-power processors enabling predictive maintenance and local AI inference.
- Semiconductor Manufacturing: Digital twin platforms improving yield, throughput, and equipment automation.
- Sustainable Energy Systems: Smart controllers enhancing grid-level DCS and renewable power integration.