Taiwan’s ASE Bets on Long-Term AI Boom With Aggressive Global Expansion, Signals Capacity Build-Out Beyond 2029

Taiwan’s ASE Technology Holding is undertaking one of the most aggressive capacity expansion programs in the semiconductor industry as it positions itself for what it believes will be years of sustained demand from artificial intelligence.

Speaking on Wednesday, Chief Operating Officer Tien Wu said the world’s largest chip packaging and testing provider is adding 15 new facilities this year, reflecting growing confidence that demand for advanced AI chips will continue to accelerate well beyond the current investment cycle.

The expansion includes six greenfield facilities for ASE, seven new sites for its subsidiary Siliconware Precision Industries (SPIL), as well as facilities acquired earlier this year from Innolux Corporation.

The scale of the buildout underscores a significant shift in the semiconductor industry. While much attention has focused on chipmakers such as Nvidia, Advanced Micro Devices (AMD), and Taiwan Semiconductor Manufacturing Company (TSMC), packaging and testing have emerged as one of the industry’s most critical bottlenecks.

Advanced AI processors require sophisticated packaging technologies that allow multiple chips, memory modules, and processors to work together at high speed while managing power consumption and heat generation. As AI models become greater and more complex, demand for these advanced packaging capabilities has surged.

Wu reiterated that ASE’s capital expenditure budget for the year stands at $8.5 billion but indicated spending could exceed that figure as the company races to add capacity.

The investment level places ASE among the biggest beneficiaries of the global AI infrastructure boom, alongside foundries, cloud providers, and data-center operators.

Notably, Wu emphasized that the expansion is not designed merely to address near-term demand.

“The factory expansion is not just for the next two years, but for 2029 and beyond,” he said, signaling management’s belief that AI-related semiconductor demand is entering a multi-year structural growth phase rather than a short-lived investment cycle.

That outlook aligns with forecasts from major technology companies, which continue to commit hundreds of billions of dollars toward AI infrastructure, cloud computing, and next-generation data centers.

ASE’s strategy also highlights the increasing globalization of semiconductor supply chains amid geopolitical pressure to localize production.

Wu said the company has already established two testing facilities in California and plans to add two more factories in the United States. The expansion was spurred by growing demand from customers seeking greater geographic diversification and aligns with Washington’s broader efforts to strengthen domestic semiconductor manufacturing capabilities.

The company is also evaluating potential investments in Arizona, one of the fastest-growing semiconductor hubs in the United States.

While Wu did not provide details, the state has become a focal point for chip investments, attracting major projects from TSMC, Intel, and other semiconductor companies seeking to build capacity closer to U.S. customers.

“At a particular customer’s request,” Wu said, ASE has been evaluating Arizona investment plans but must carefully assess the scale and nature of any future commitment.

ASE has been in a growing relationship with Nvidia. Last year, Nvidia announced plans to help build as much as $500 billion worth of AI server infrastructure in the United States through a network of manufacturing and supply-chain partners that includes Siliconware Precision Industries.

SPIL is one of Nvidia’s key packaging suppliers and plays an important role in preparing the advanced processors used in AI servers and data centers.

Yet despite Nvidia’s massive U.S. infrastructure ambitions, SPIL has not formally announced a major American investment tied to the initiative. That suggests the company remains cautious about balancing customer requirements, capital allocation, and long-term utilization rates before committing to large-scale overseas expansion.

The broader significance of ASE’s expansion lies in what it reveals about the next phase of the AI race. While much of the attention has focused on training ever-larger AI models, the industry’s ability to scale increasingly depends on physical infrastructure and manufacturing capacity. Packaging and testing have become strategic assets because they determine how quickly advanced chips can move from production lines into AI servers.

Industry analysts now see advanced packaging as one of the most valuable segments of the semiconductor value chain. The scarcity of packaging capacity has, at times, constrained shipments of AI accelerators even when sufficient wafers were available from foundries.

ASE’s willingness to spend more than $8.5 billion and potentially exceed that amount is seen as an indication of confidence that demand from hyperscalers, cloud providers, and AI developers will continue to outpace supply for years.

The company’s expansion plans also provide another indication that semiconductor suppliers expect AI spending to remain robust well into the next decade, with capacity decisions now being made based on demand projections extending beyond 2029 rather than merely responding to the current surge in orders.