There is a peculiar irony at the heart of AI infrastructure. The chips generating the most excitement in financial markets — the GPUs at the centre of every earnings call and capital allocation decision — cannot function until an entirely different set of semiconductors solves a problem most investors have never considered.
The Re-Rating Thesis
Every watt of power consumed by an AI accelerator must be transformed, regulated, protected, and delivered with extraordinary precision before a single calculation occurs. The companies making this possible are, in aggregate, less discussed than the GPU designers they serve. They are also, in several important cases, more defensibly positioned — because their revenues accrue regardless of which GPU vendor wins the AI compute race. Every rack pays the same toll to the same supply chain.
The physics is straightforward. Two equations explain why the entire power semiconductor supply chain must be re-engineered. First: P = V × I — power equals voltage multiplied by current. As AI racks push from 120 kilowatts toward one megawatt, the industry faces a choice: deliver that power by increasing current, or by increasing voltage. The previous generation chose current — running at 54 volts and pushing thousands of amps through copper. But the second equation determines why that approach has hit a wall: Ploss = I² × R — waste heat in copper scales with the square of the current. Double the current, quadruple the loss. At megawatt scale, the copper alone would weigh 200 kilograms per rack. The only viable path forward is to raise the voltage — from 54V to 800V — which cuts the required current by roughly 15×, slashing resistive losses by over 200×. This voltage transition is not a design preference. It is a law of physics, and it structurally requires silicon carbide and gallium nitride semiconductors that silicon cannot replace.
The sector was mispriced as an electric vehicle cyclical. When EV demand slowed in 2023, the market treated the entire power semiconductor industry as broken. It was not broken — it was incomplete. The EV recovery remains on track, with next-generation 800V vehicle platforms driving meaningfully higher semiconductor content per car. But two additional demand vectors — AI infrastructure and grid decarbonisation — have since emerged that were absent from every 2022 bull case. The market is currently pricing AI infrastructure power semiconductors as one recovering cyclical. The report argues that mispricing is the investment case.
A note on valuation: Several of the names highlighted in this report have already re-rated meaningfully from their 2023–2024 troughs. We acknowledge the initial move. Our thesis, however, is that the earnings inflection ahead — driven by the structural 54V-to-800V transition and the emergence of AI and grid demand — will dwarf the share-price recovery seen so far. More importantly, if this demand proves secular rather than cyclical, these companies deserve a fundamentally different multiple. The absence of the boom-bust pattern that has historically compressed power semiconductor valuations is itself a source of future capital appreciation that the market has not yet priced in.
Market at a Glance
Sources: Mordor Intelligence (2026), Global Market Insights (Mar 2026), SNS Insider (Apr 2026) for TAM; Yole Group Power SiC 2025 and Power GaN 2025 for sub-segment forecasts; company reported financials for hyperscaler capex. GaN figure reflects broader power market including consumer; Yole power-device segment only ~$355M in 2024. All forecasts subject to revision.
Why the Transition Is Happening Now — Four Forcing Functions
The Full Value Chain — Where Value Concentrates and Where It Doesn't
| Layer | Description | Key Players | Investment Rationale | Risk / Chokepoint |
|---|---|---|---|---|
| Raw Materials | The raw crystals and elements from which power chips are made | Wolfspeed, Coherent, ROHM/SiCrystal for SiC; China controls ~80% of gallium supply | SiC supply constrained through 2027. China's 2023 export controls on key materials remain an active risk. | China export controls on key materials. Wolfspeed — the leading independent SiC substrate supplier — has been under significant financial pressure, highlighting how concentrated and fragile parts of this supply chain remain. |
| Epitaxy Equipment | Specialised crystal-growing reactors (HTCVD for SiC, MOCVD for GaN) | ASMI/LPE (SiC epi); AIXTRON (GaN/SiC MOCVD); Naura (CN) | 12–18 month switching costs lock in customers. Current trough = entry point. Recovery expected 2027–2028. | Chinese competition advancing. SiC oversupply extending. GaN ramp timing uncertain. |
| Back-End Substrates | Ceramic tiles that sit between a power chip and its metal housing, conducting heat away | Maruwa (5344.T) ~15% global share; Kyocera; Rogers; Denka — three-player oligopoly | The chokepoint device-layer analysis misses. Even perfect SiC ramp execution at Infineon and onsemi cannot outrun Si₃N₄ substrate constraints. Maruwa: ~15% global share, ~45% OPM on highest-growth segment. Three-player oligopoly. Under-monitored by most Western analysts. | Expanding capacity requires specialist equipment with multi-year lead times. Most Western investors have never heard of this company. |
| Power Device (IDM) | The actual silicon carbide and gallium nitride chips that do the voltage conversion | Infineon, onsemi, STMicro, ROHM, Wolfspeed, Navitas | Infineon holds the primary GPU power position. SiC recovery underway from 2025–2026 trough. GaN gaining share in AI power supplies. | Must re-win position with each new GPU generation. Chinese competition compressing margins in standard silicon products. |
| Protection & Isolation ICs | Safety and control chips — supervise power flow and protect circuits from faults | Analog Devices (ADI), Texas Instruments, Littelfuse | ADI grows regardless of which GPU power supplier wins. TXN present at multiple stages of every AI rack. | Slower growth than chip-level names during peak cycles. China competitive at lower-end products. |
| System Integration | Complete power delivery units — power supplies, distribution panels, backup systems, next-gen modules | Delta Electronics (2308.TW), Flex Power, Bel Fuse, Murata, ABB | Delta bridges the device layer and hyperscaler infrastructure. Buys power semiconductor components from manufacturers such as Infineon and onsemi and assembles them into the complete power delivery hardware — server power supplies, rack distribution units, and backup power systems — that hyperscalers physically install in their data centres. Infineon–Delta VPD collaboration is the concrete illustration of cross-layer value chain interaction. | Delta has warned of rising input costs — driven by oil and the same AI demand fuelling its revenues. TWD/USD currency exposure adds volatility. |
Where Value Actually Concentrates
Highest-quality moats: Equipment incumbency (ASMI, AIXTRON) — 12–18 month switching costs protect revenue across cycle turns, entry at trough. Protection infrastructure (ADI, TXN) — grows with GPU power density, generation-agnostic, no socket reset risk. System integration (Delta) — less volatile than pure device names, direct AI CapEx linkage.
Hidden chokepoint: Maruwa's ceramic substrates — a near-oligopoly upstream of the chip manufacturers that standard analysis ignores. Worth tracking before the next SiC expansion wave makes the constraint visible.
Avoid: Commodity Si MOSFET and standard packaging — Chinese vendors closing the quality gap with state subsidy. Margin compression is structural, not cyclical.
Highest near-term leverage: Chip-level GPU power positions (Infineon, MPWR, Vicor) carry the highest earnings upside from platform wins — and the highest risk of disruption when NVIDIA changes generations. These are event-driven positions, not long-term compounders.
Silicon Hits a Wall — and Wide-Bandgap Materials Step In
Most electronics run on standard silicon chips. Silicon works well for most applications. But it has a hard ceiling: above a certain voltage and temperature, it wastes too much energy as heat and simply stops working efficiently. AI data centres and electric vehicles have now pushed past that ceiling. Two newer materials — silicon carbide (SiC) and gallium nitride (GaN) — handle much higher power levels with far less heat loss. They are not upgrades to silicon; they are replacements built for a different class of problem.
† GaN voltage range reflects current commercial devices (650V lateral GaN widely available; 900V devices shipping). Vertical GaN architectures — including onsemi's GaN-on-GaN platform announced October 2025 — are pushing beyond 1.2kV, directly targeting 800V data centre and EV applications.
NVIDIA's GPU Roadmap — Power Demand Doubles With Every Generation
Why the Next Generation of AI Servers Needs a Fundamentally Different Power Design
A GPU chip runs at less than one volt — roughly the voltage of a AA battery — but a next-generation AI rack consumes up to 600,000 watts. Delivering that much power at such a low voltage means pushing an enormous amount of electrical current through the system. The problem: copper wiring resists current flow, generating heat. Even a short section of circuit board trace wastes 800 watts at these current levels — roughly the heat output of a small electric heater, concentrated in a few centimetres of wire.
The underlying constraint is the relationship between power, voltage, and current: P = V × I. At today's 54-volt rack architecture, delivering 120 kilowatts requires over 2,200 amps. The heat wasted in copper conductors scales with the square of the current (I²R), so every increase in rack power drives a disproportionate increase in waste heat and copper mass. At megawatt scale, 54V distribution would require up to 200 kilograms of copper busbar per rack — the weight of the rack structure itself. The industry's response is to raise the distribution voltage from 54V to 800V, reducing the required current by approximately 15× and cutting I²R losses by over 200×. This is the same principle that drives long-distance electricity transmission at hundreds of thousands of volts. It is also why this transition structurally requires wide-bandgap semiconductors — silicon carbide and gallium nitride — which can operate efficiently at these higher voltages where standard silicon physically cannot.
The solution — now being adopted across the industry — is to move the final voltage conversion step from the edge of the circuit board to directly beneath the chip itself, shortening the current path from several centimetres to a few millimetres and eliminating most of that heat loss. This is called Vertical Power Delivery (VPD). It is not a design choice; it is what the physics demands at the power levels the next generation of AI hardware requires.
Six Conversion Stages, Six Toll Booths — GPU-Vendor Agnostic Revenue
Electricity from the grid cannot go straight into an AI chip. It must pass through six separate conversion and regulation stages — each one stepping down the voltage and managing the power more precisely — before reaching the chip at the correct level. Think of it as a series of six toll booths on the road from the electricity grid to the GPU. Each toll booth is a separate commercial opportunity, served by different companies, generating revenue regardless of which chip manufacturer wins the AI race.
| # | Stage | What Happens | Who Benefits | Why It Matters |
|---|---|---|---|---|
| 1 | Grid Entry — Grid → data centre | Grid electricity is converted to high-voltage DC for distribution across the data centre. Current Blackwell systems use 54V DC in-rack distribution; the industry is preparing to upgrade to 800V starting with Vera Rubin, mandatory at Kyber / Rubin Ultra scale. | Infineon (SiC), STMicro, onsemi, Wolfspeed, Power Integrations (POWI), Navitas Semiconductor | Every AI campus built to the forthcoming 800V standard will require SiC and GaN chips at this stage regardless of GPU vendor. GaN-based rectification (POWI, Navitas) enables the 98%+ efficiency targets that make 800V systems economically viable at megawatt scale. |
| 2 | Bus Protection — safety & protection | Safety components that monitor the high-voltage power line and protect the rest of the system from faults or spikes. Present in every rack, regardless of which GPU or power supplier is used. | Analog Devices (ADI) dominant · Texas Instruments | ADI earns revenue regardless of who wins the GPU power competition. Every converter made by any supplier still needs ADI's safety components. |
| 3 | Intermediate Bus — step-down for distribution | Steps the high voltage down to a lower level (48V) for distribution across the server. GaN semiconductors are enabling smaller and more efficient converters than the previous generation of silicon-based designs. | Vicor (FPA), Infineon (CoolSiC), Renesas, TI | The entire hyperscaler industry is mid-transition to 48V systems. GaN is the enabling technology. This is where GaN's commercial momentum is most visible today. |
| 4 | Point-of-Load VRM — final step to GPU chip | The final step — reducing voltage to the tiny fraction of a volt the GPU actually runs at, while pushing an enormous amount of current. This is the most commercially valuable component position in the chain. Suppliers must compete for it afresh with each new NVIDIA GPU generation. | Infineon (Vera Rubin primary) · Renesas (secondary) · MPWR (requalifying) · Vicor (Kyber VPD) | The key competitive battle. Who wins this position with NVIDIA determines the biggest earnings swings in the sector. |
| 5 | Energy Storage — power shock absorber | Acts as a buffer between the power supply and the GPU — absorbing sudden spikes in electricity demand when AI workloads ramp up instantly. Think of it as a shock absorber for electricity. | AOSL, Texas Instruments, Eaton, Delta Electronics | AOSL has exposure to both AI server power delivery and optical networking — two fast-growing AI themes. This combination is not yet fully reflected in its valuation. |
| 6 | Upstream Equipment — crystal growth reactors | Specialised reactors that grow the semiconductor crystals from which all power chips are made. Once a chipmaker qualifies a reactor for their production line, switching costs (12–18 months of re-testing) are prohibitively high. | ASMI/LPE (SiC) · AIXTRON (GaN) | Near-duopoly with deeply entrenched customer relationships. Current oversupply in SiC creates an entry opportunity ahead of a recovery expected around 2027. |
The Layer 4 Socket Race — The Single Most Proximate Catalyst
Infineon — the incumbent (Vera Rubin primary). Direct architecture collaboration with NVIDIA on next-generation 800V DC power delivery makes within-generation displacement very difficult. CoolMOS and CoolSiC platforms benchmark best-in-class for high-current GPU VRM synchronous rectification. Kyber path depends on VPD compatibility of next-generation platform.
Renesas — the qualified second. Co-qualified across Blackwell and Vera Rubin. Automotive VRM heritage translates directly to AI demands. Path to primary requires Infineon execution failure or a VPD transition that resets the competitive field.
Vicor — the long-duration VPD option (Kyber H2 2026). Factorised Power Architecture places the Voltage Transformation Module directly beneath the GPU package substrate — the exact topology Vertical Power Delivery demands. Architecture-matched. Execution unproven at hyperscaler volume. Kyber specification finalisation in H2 2026 is the defining binary event.
Tiber (private) — the wildcard. Substrate-embedded voltage conversion could change the physical form of the Layer 4 socket entirely if adopted at Vera Rubin or Kyber scale. A monitoring item for all VRM positions with a 2027–2028 risk horizon.
Six Risks That Could Break the Thesis
Please refer to our full disclaimer for important disclosures and regulatory information.
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