The global semiconductor industry is undergoing a profound restructuring driven by artificial intelligence—but this transformation is far from uniform. Behind surging NVIDIA GPU orders, TSMC’s fully booked CoWoS capacity, and accelerated HBM4E development lies a deepening structural imbalance: advanced packaging lags behind chip design, critical materials face geopolitical constraints, and second-tier players struggle to scale amid capital intensity.
The most acute tension manifests in physical implementation. Take NVIDIA’s Blackwell platform: built on TSMC’s CoWoS-L packaging, integrating 208 billion transistors and relying on HBM3E memory from Micron and SK Hynix. Yet OSAT providers like Amkor cannot expand packaging capacity fast enough to meet demand. CoWoS utilization has remained above 98% for six consecutive quarters since late 2025, with new capacity requiring at least 18 months to come online. This means even if NVIDIA designs more powerful chips, mass deployment remains bottlenecked. I judge that by late 2026, the industry will face a “design-ahead, packaging-behind” delivery crisis, forcing customers to accept performance compromises or delayed rollouts.
Material supply chains are equally fragile. Ultra-pure silicon, advanced photoresists, and low-k dielectrics remain concentrated in few hands. Japanese firms control over 90% of the global photoresist market. While SandboxAQ’s quantum-simulation collaboration with TSMC promises to accelerate materials discovery, commercialization is still nascent. More critically, logistics are vulnerable to geopolitical friction. In 2025, Red Sea shipping disruptions delayed deliveries of argon fluoride gas for EUV lithography, halting a Taiwan, China wafer fab for two weeks. Such “invisible disconnections” are shifting procurement strategies from cost-driven to resilience-driven.
Second-tier players are exploiting these imbalances. Samsung has abandoned FinFETs entirely, pivoting to gate-all-around (GAA) vertical transistors, and opened real-time fab data feeds to equipment suppliers to accelerate yield ramp. SK Group, meanwhile, scrapped degree requirements and introduced equity incentives to attract AI chip talent—its valuation now exceeds KRW 2,000 trillion. These moves signal that dominance isn’t immutable. In HBM and advanced packaging, Samsung and SK Hynix leverage their memory leadership to build integrated “memory-packaging-system” solutions, challenging TSMC’s CoWoS hegemony.
Geopolitics amplifies these strains. Taiwan, China’s 2026 GDP growth could reach 10%, largely fueled by AI chip exports—but this also makes it a focal point of strategic competition. Penang, Malaysia, aims to capture backend packaging capacity, yet local firms like Galatek cite insufficient deep-tech infrastructure and IP protection as barriers to value-chain ascent. In contrast, an experimental RISC-V chip project by GigaDevice, Infineon, and the University of São Paulo explores embedding rainforest-derived biomaterials into substrates—a fringe but symbolic effort by Global South actors to pursue technological autonomy.
Even EDA tools aren’t immune. Synopsys’ Design IP revenue fell 7% year-over-year in 2025 as it redirected resources toward AI-powered verification, sacrificing traditional IP licensing. This raises costs for smaller chipmakers and elevates innovation barriers. Cadence and Keysight are capitalizing by strengthening system-level simulation, aiming to close the “design-test-manufacturing” loop. The EDA triad’s strategic pivot is quietly reshaping chip design fundamentals.
In sum, AI compute expansion hasn’t delivered synchronized prosperity across the semiconductor value chain. Instead, it has exposed and intensified vulnerabilities. The real contest no longer hinges solely on transistor density or TOPS—it’s about who can orchestrate end-to-end synergy across materials, manufacturing, packaging, and systems. Over the next 18 months, the industry will enter a period of deep recalibration: either bridging gaps through capital-technology coupling or fracturing into new ecosystems. A pivotal question looms: as AI chips approach the physical limits of Moore’s Law, can the industry find sustainable growth in a “new Moore cycle” driven by packaging and materials innovation?