Packaging gap closes as AI supply chain drains MLCC availability

While AI-demand-driven shortages have primarily impacted advanced processors and memory, the rapid expansion of supporting infrastructure is also increasing pressure on semiconductor packaging technologies and essential passive components. As companies race to increase their AI capabilities, the industry is working in parallel to address these emerging constraints.

But the news is not all bad. Recent developments indicate that some bottlenecks are finally easing. TSMC's efforts to expand CoWoS advanced packaging capacity are panning out, and its popular CoWoS packaging is finally closing the supply-demand gap.  

CoWoS capacity expansion eases AI packaging constraints

For most of the past two years, CoWoS has been one of the most contested choke points in the AI supply chain. The packaging technology has become so central to high-performance AI accelerator production that demand for it has consistently outpaced what TSMC and its partners can deliver. After intense effort to expand CoWoS capacity, that dynamic is starting to shift.  

According to institutional investors cited by Economic Daily News, the CoWoS supply-demand gap is expected to narrow from roughly 20% today to 10% by the end of 2026. Further improvement is also anticipated heading into 2027.  

TSMC’s monthly CoWoS output is projected to reach a record 120,000 to 140,000 wafers this year. When combined with additional wafers from OSAT partners, total industry capacity could approach 200,000 wafers monthly. Such a figure was nearly unthinkable just a few years ago.

The increase reflects both TSMC’s capital investment and the degree to which the broader semiconductor packaging segment has been uplifted by the AI infrastructure buildout.  

TSMC forecast during its Taiwan Technology Symposium in May that CoWoS capacity will achieve a CAGR of more than 80% from 2022 to 2027, signaling a sustained trend that doesn’t occur without equally sustained demand. Driven overwhelmingly by AI accelerator orders from hyperscalers, that demand shows no signs of weakening.  

CoWoS is irreplaceable in this context thanks to its role as the integration layer between leading-edge processors and high-bandwidth memory. The packaging technology enables AI accelerators to feed enormous memory bandwidth to the compute centers for inference and training work by placing HBM stacks in close physical proximity to the GPU. This drastically reduces latency and power consumption relative to traditional packaging capacities.  

Though there is no near-term substitute, TSMC is already developing its next-gen Chip-on-Panel-on-Substrate (CoPoS) packaging platform through its VisEra subsidiary. According to TrendForce, material and equipment qualification is expected as early as this month, with the first pilot production lines spinning up in mid-2027. Nvidia’s Feynman platform is expected to be the first major adopter as early as 2028.  

For now, the narrowing supply-demand gap in CoWoS is encouraging, but a 10% imbalance is still a noteworthy constraint in the market. Procurement teams managing AI hardware programs can look at this trajectory in a positive light, but the window for securing allocation without lead-time risk has not yet closed.  

MLCC shortages deepen as AI demand expands

Beyond the semiconductors grabbing headlines, a different class of components is now flashing warning signs in the face of booming AI demand. Despite being present in virtually every electronic device, multilayer ceramic capacitors (MLCCs) are rarely a focal point. Now, industry warnings are escalating, as are lead times.  

MLCCs are unglamorous passive components, but their role in power delivery and signal filtering makes them non-negotiable in AI server architectures. As has become the new norm across segments, AI servers require significantly higher volumes of passive components, including MLCCs, driving consumption to new levels.  

Bill Tang, chairman of Taiwan-based MLCC supplier Holy Stone Enterprise, recently told Digitimes that demand for high-end MLCCs has reached levels not seen in over two decades. Lead times have already extended beyond 20 weeks, and supply conditions are expected to worsen over the next 18 months.  

Current capacity additions from major MLCC producers are unlikely to fully offset demand growth from AI server deployments through 2027. As a result, companies managing long production cycles or those reliant on high volumes of MLCC face a double-edged predicament as extended lead times compound pressures from an already-strained supply chain.  

As is the case in memory, manufacturers are increasingly prioritizing production at premium tiers for AI server customers. This has compressed availability for automotive, industrial, and consumer electronics buyers who are competing for MLCC from the same manufacturers. If the memory shortage has taught any lesson, it is that hyperscale buyers tend to win out when inventory becomes scarce.  

Until recently, most procurement teams managed MLCCs with minimal difficulty, but that trend is changing now as AI demand realigns where production capacity goes. Most organizations have clear visibility into their semiconductor exposure but lack equivalent insight into passive components. When lead times stretch without warning, this blind spot can become costly.  

For now, the broad implication is that AI demand is creating bottlenecks in categories other than processors and memory, though they often get far less attention. Procurement leaders should review MLCC-heavy BOMs now and identify qualified alternates before lead times extend further. Relying on the assumption that historical availability patterns will hold through 2026 and into 2027 could be a costly mistake.  

Sourceability helps businesses reduce supply risk through global sourcing capabilities, alternative component identification, inventory management solutions, and real-time market intelligence that supports proactive procurement decisions. As AI demand continues to reshape the chip industry, partnering with Sourceability can help ensure your supply chain stays ahead of the disruptions that are still to come.