MLCC Shortage Is Reshaping AI Hardware Supply Chains

The Bottleneck No One Saw Coming

MLCCs — the tiny ceramic chips embedded in virtually every electronic device — are the most overlooked component in the AI hardware supply chain. They are cheap, unglamorous, and everywhere. Until now, no one was running out of them.

That has changed. AI servers draw roughly ten times more MLCCs than conventional servers. The infrastructure buildout powering large language models, real-time inference engines, and sprawling GPU clusters is creating a demand shock that capacitor makers simply cannot satisfy fast enough.

Samsung Electro-Mechanics reported in late July that its MLCC average selling price rose 13.9 percent year-over-year in the first half of 2025, while production-line utilization hit 91 percent — near maximum capacity. The company has locked in long-term supply agreements with more than a dozen global customers and has already hiked distribution-channel prices by roughly 10 percent in June and another 30 percent on select products this month. Prices are climbing because scarcity is real, not manufactured.

The implication is broader than a component squeeze. When a single bottleneck cascades through the highest-growth segment of the semiconductor industry, it forces redesigns, alternatives, and — ultimately — new market winners.

A Korean Pivot From MLCC to Supercapacitor

Kochip, a South Korean chipmaker known primarily for MLCC distribution, is reading the same signal and choosing a different path. The company said on July 28 that it is actively approaching potential buyers in AI servers, data centers, robotics, and autonomous driving to introduce supercapacitors as a complementary — and in some cases, substitutable — power-storage solution.

A Kochip executive confirmed that no contracts have been signed yet. But the outreach is happening across multiple verticals simultaneously, and the strategic logic is clear: if MLCCs are chronically constrained and pricing upward, a different class of capacitor that handles high-power, high-heat environments well may carve out its own market before the supply gap closes.

Supercapacitors are not a perfect substitute for MLCCs — they serve different electrical functions. But they share the same customer base in power-delivery subsystems, and they offer distinct advantages where AI hardware demands rapid charge-discharge cycles and burst power delivery. That makes supercapacitors viable for load-leveling in server power supplies, regenerative braking in robotics, and transient-power buffering in autonomous-vehicle control units.

The timing matters. The AI infrastructure buildout is measured in quarters, not years. Any component strategy that moves from internal exploration to commercial delivery within 12 to 18 months could ride the current demand wave. Anything slower arrives after the cycle turns.

Samsung Electro-Mechanics: The MLCC Incumbent

Samsung Electro-Mechanics is the dominant force in the MLCC space, and its recent deal to supply silicon capacitors for AI semiconductors to major U.S. tech firms — widely reported in June — underscores the intensity of the competition for power-management components in AI hardware.

Kochip’s executive declined to comment on specifics of that deal but acknowledged that the broader market expansion creates upside for all domestic capacitor manufacturers. In effect, Samsung Electro-Mechanics is capturing the high-end MLCC premium, while Kochip is exploring whether a second-tier player can establish a foothold in supercapacitors before incumbents fully commit to the category.

That is a narrow window. Global supercapacitor demand is growing, but so is competition from Japanese and Chinese manufacturers who already produce these devices at scale. Kochip’s differentiation will depend on two things: its ability to design supercapacitor modules optimized for the thermal and power-profile requirements of AI data-center hardware, and its willingness to sell volume at margins thin enough to compete but thick enough to fund further R&D.

Neither is guaranteed.

Who Wins and Who Loses

The winners in this dynamic are companies that can either solve the MLCC shortage or offer a credible alternative before demand outstrips available capacity. Samsung Electro-Mechanics is well-positioned on the MLCC side, with utilization near maximum and pricing power intact. Any OEM or systems integrator that has secured long-term supply agreements will face lower short-term risk than those relying on spot-market purchases.

On the alternative-side, supercapacitor manufacturers stand to benefit — but only if they can transition from component supplier to system-level partner. The companies that win will be those that work closely with server designers and autonomous-vehicle engineers early enough to shape module specifications around their own product capabilities.

Kochip is attempting that transition. Whether it succeeds depends on execution speed and the depth of its engineering partnerships. No contracts have been signed, and the company itself frames the effort as exploratory.

The losers, for now, are buyers on the spot market. MLCC prices are rising, lead times are lengthening, and there is no indication that new capacity will come online fast enough to reverse the trend. Server OEMs and robotics manufacturers without secured supply agreements are absorbing the cost.

What Comes Next

The MLCC shortage is unlikely to resolve in the next twelve months. AI server deployments are accelerating, not plateauing, and capacitor demand scales linearly with GPU count. Even aggressive capacity expansion by major producers will take time to materialize, and new fab construction is capital-intensive and slow.

Supercapacitor adoption in AI hardware will therefore be incremental rather than transformative in the near term. It is more accurate to think of it as an emerging hedge — a diversification strategy for procurement teams that want to reduce dependence on a single component class during a period of sustained shortage.

The market will reward clarity. Companies that can demonstrate supercapacitor modules validated for data-center power systems will earn specification wins. Those that continue to rely solely on MLCC spot purchases will face margin pressure and delay risk as component availability remains tight.

Kochip’s pivot is a signal that the AI hardware supply chain is entering a phase of active reconfiguration. The question is not whether alternative power-storage technologies will gain traction — they already are. The question is who will secure the partnerships and certifications needed to convert exploratory outreach into commercial reality before the next capacity constraint emerges.

In this market, speed is the only advantage that compounds.