As the global AI arms race continues to intensify, the fragility of the chip supply chain has once again come into focus. Meanwhile, energy and raw material supply pressures caused by conflicts in the Middle East are adding new uncertainties to the global semiconductor industry.

As a major manufacturer of high-end AI chips, TSMC acknowledged as early as January this year that its capacity is tight. The surge in AI infrastructure development has heavily occupied its advanced process production lines. The world’s largest semiconductor foundry, whose major clients include Nvidia and Apple, also stated that it is working to narrow the supply-demand gap.

TSMC plans to continue expanding capacity through 2027. However, in 2026, its capacity has already become a bottleneck, effectively constraining the entire supply chain. The issue of supply chain tightness is no longer limited to chips alone but has spread across multiple segments of the broader technology industry.

To ensure production stability over the coming years, many customers are being forced to shift toward long-term agreements. Currently, a growing number of clients are signing capacity assurance contracts lasting three to four years. This trend has also been confirmed by memory chip giant Samsung Electronics. Last week, Samsung stated that it is working with key clients to extend cooperation agreements to three to five years. This move reflects both customers’ demand for long-term supply security and suppliers’ desire to hedge against fluctuations in market demand.

TSMC’s capacity bottleneck is also evident in its most advanced 2nm process. Reports indicate that demand for TSMC’s 2nm capacity far exceeds supply. Even its largest client, Nvidia, may be forced to redesign its next-generation AI chip platform “Feynman.” Originally scheduled for release in 2028 as the successor to the current Vera Rubin architecture, any redesign due to capacity constraints could impact its performance targets, launch timeline, and cost structure.

At the same time, tech giants such as Meta have joined the competition for 2nm capacity, further intensifying the supply-demand imbalance. As a result, order schedules for TSMC’s advanced processes have already been pushed beyond 2028.

Capacity shortages have also given TSMC stronger pricing power. Its advanced process nodes are expected to see continuous price increases over the next four years. This means chip designers will not only face supply shortages but also rising manufacturing costs. These costs will ultimately be passed on to AI server manufacturers, cloud service providers, and end-user enterprises, further driving up the cost of deploying AI infrastructure.

Market Analysis:
Taiwan’s chip manufacturing industry contributes about one-fifth of its economic output, but the entire ecosystem is highly dependent on imports. Taiwan’s energy supply heavily relies on the Middle East, with 97% of its energy needs imported and 37% of its liquefied natural gas sourced from the region. TSMC alone accounts for about 10% of Taiwan’s total electricity consumption, and advanced manufacturing processes require extremely stable power supply—even millisecond-level fluctuations can result in wafer defects and losses.