When Will the AI Shortage End? How Capital and Capacity Impact Your Strategy

Two iconic figures in the semiconductor industry, Broadcom CEO Hock Tan and Intel CEO Pat Gelsinger, have provided a clear timeline for the development bottlenecks of Artificial Intelligence (AI). They agree that the global wafer capacity shortage currently plaguing the industry is not expected to see significant improvement until 2028 or 2029. This prediction serves as a reminder to companies planning digital transformations that AI hardware supply cannot be achieved overnight, and this "waiting period" will be a critical window for adjusting internal IT architectures.

Realistic Challenges of Wafer Foundry and Capacity

Building a wafer fab requires an extremely long lead time. From land acquisition and plant construction to equipment installation and yield tuning, the cycle typically takes three to five years. Even as global semiconductor giants announce expansion plans, this new capacity will only provide a stable supply after 2028 at the earliest. For enterprises requiring massive computing resources, this means the procurement cost of high-performance servers may remain high in the short term, with longer lead times. We recommend that decision-makers consider flexibility in hardware acquisition when evaluating AI projects and avoid over-reliance on a single hardware supply chain.

Capital Constraints Replace Technology as the Biggest Bottleneck

The CEOs emphasized that future bottlenecks may not lie in "whether the technology is achievable" but in "whether capital is sufficient." The cost of an advanced process wafer fab reaches tens of billions of dollars, posing a severe test for corporate financial strategies. When capital becomes the primary constraint driving technological progress, a company's Return on Investment (ROI) will be under intense scrutiny. Pursuing high-spec hardware blindly without corresponding application scenarios or software optimization will turn high amortization costs into a financial burden. In our experience serving clients, software optimization and a sound IT services architecture can often achieve performance close to next-generation equipment using existing hardware foundations.

How SMEs Can Respond During the Waiting Period

Before capacity eases in 2028, Taiwanese SMEs should not adopt a "wait-and-see" strategy. On the contrary, this is the best time to inventory IT assets. First, you can re-examine existing server utilization and distribute computing pressure through virtualization technology or hybrid cloud architectures. Second, AI implementation does not necessarily have to start with heavy hardware; many lightweight language models and ready-made AI services are already sufficient to support daily business needs. The key is how to integrate these tools into existing workflows rather than waiting for hardware prices to drop years from now. We observe that companies that start building data infrastructure earlier are better able to transition seamlessly and generate business value when hardware capacity is released in the future.

Optimizing Investment Benefits with IT Services

When hardware resources become scarce and expensive, the professional value of IT services lies in "maximizing resources." We help enterprises evaluate appropriate system scales to avoid capital waste caused by over-construction. From website development to backend AI server deployment, overall IT environment optimization can help you maintain digital competitiveness even in a capital-constrained environment. Facing the period of change over the next four to five years, robust architectural design and flexible technological layout will be the keys for enterprises to stand out in the AI wave.

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