Infineon Technologies AG, one of the world's largest analog chip manufacturers headquartered in Germany, announced robust quarterly results and a future outlook on Wednesday. The company's management stated in its outlook that it will significantly increase technology and production capacity investments targeting hyperscale AI data centers, aiming to achieve revenue growth as global enterprise demand for AI computing solutions accelerates exponentially. Infineon currently plans a total investment of approximately €2.7 billion (roughly $3.2 billion), exceeding both the institution's prior expectations and the consensus analyst forecast of around €2.2 billion.
Infineon stated in its Wednesday announcement that it expects overall revenue from the data center sector could grow from about €1.5 billion in the current fiscal year—representing roughly 10% of total revenue—to at least €2.5 billion by 2027. "This would equate to increasing our AI data center-related sales tenfold within just three years," Infineon's CEO, Jochen Hanebeck, told analysts during Wednesday's earnings call.
Buoyed by the strong results and future outlook, Infineon's stock price rose as much as 4.2% at the opening of trading on the Frankfurt stock exchange. Infineon's latest strong performance and outlook further reinforce the recovery trajectory in analog chip demand, led by Texas Instruments, STMicroelectronics, and NXP—a recovery trend overwhelmingly driven by the vigorous AI data center construction efforts of tech giants like Google, Microsoft, and Meta.
Particularly, the robust earnings from Texas Instruments and Infineon, coupled with the record-breaking stock performance of the dominant leader in the analog chip sector, Texas Instruments, amidst global market volatility, collectively highlight that the seemingly "endless" chip demand from AI training and inference, fueled by the unprecedented AI wave, is successfully transferring from AI chips and memory chips to the analog chip segment. This is powerfully driving the earnings of analog chip leaders like Texas Instruments, Analog Devices, Infineon, and NXP towards a strong recovery trajectory.
Regarding overall revenue figures, Infineon reported total revenue of approximately €3.66 billion for the first quarter of fiscal 2026, ended December 31, representing a 7% year-over-year increase and slightly surpassing the average analyst estimate of around €3.62 billion. The adjusted operating margin was approximately 17.9%, higher than the average analyst expectation of 16.8%, which had been revised upwards recently. Revenue from the company's long-sluggish automotive business also slightly exceeded average analyst expectations, reaching about €1.8 billion.
For other key performance metrics, Infineon's Q1 operating profit was approximately €256 million, up about 5% year-over-year, slightly above the average analyst forecast; adjusted earnings per share for the first quarter were about €0.35, higher than the already strong €0.33 from the same period a year prior and also exceeding average analyst expectations.
The company's statement quoted its CEO, commenting: "While other market backdrops are relatively weak, demand from AI data centers is very active, providing us with an exceptionally strong tailwind." The strong rise in AI data center demand is helping Infineon counterbalance its long-weak automotive chip business—historically its largest segment, accounting for about half of total sales, but which has been sluggish since late 2022.
Investors have been awaiting a recovery in these more mature chip businesses, following several consecutive quarters of significant revenue declines in the analog chip sector, primarily driven by prolonged weak demand, especially as automotive chip customers worked through inventory built up during the supply shortages of the COVID era. In November last year, Infineon management stated that data center-related sales in 2026 would be double those of 2025, following a tripling of growth in the preceding year.
To further diversify its chip business, Infineon said late Tuesday that it had agreed to acquire the automotive, industrial, and medical sensor business of ams-OSRAM for $673 million in cash. These types of sensors are used for detection, converting signals like motion and sound into data, and are applied in vehicles, health trackers, and a future growth engine Infineon is focusing on—humanoid robots. The transaction, to be financed through new debt, is expected to generate sales of approximately €230 million in the current calendar year.
Regarding market-focused earnings expectations, the company's management stated that revenue for the current period would be approximately €3.8 billion, slightly above the average analyst estimate range, further reinforcing the analog chip demand recovery trajectory led by giants like Texas Instruments. Infineon expects its adjusted operating margin for the quarter to be in the mid-to-high end of the 15% to 20% growth range, broadly in line with the average analyst estimate of 17.5%.
The company reiterated the outlook provided in November last year: achieving "moderate revenue growth rates" in the fiscal year ending September 2026. Senior analysts at Citi, including Andrew Gardiner, wrote in their commentary on Infineon's earnings: "A cyclical strong recovery is evident in Infineon's results, but similar to analog chip peers, the recovery is slower and varies by end-market compared to US chip counterparts like Nvidia, Broadcom, and Micron. For analog chip manufacturers like Infineon, the clarification of growth prospects closely tied to artificial intelligence is undoubtedly a long-term positive factor."
Infineon's CFO, Sven Schneider, stated that analog chip technology serving AI data centers has "tremendous growth potential." "This number is rising quarter by quarter; for us, it's one of the largest growth drivers in the company's history," Schneider said during the earnings conference. Infineon's business is similar to that of the world's largest analog chip giant, Texas Instruments; both possess "analog/power-related" chip DNA, with businesses largely concentrated on analog and power devices essential for data centers, industry, and automobiles.
Rising power consumption in AI data centers is increasing demand for components like power conversion, power supply protection, monitoring, and drivers, which is why both analog chip companies have recently emphasized data center/AI-related demand pull in their public narratives. However, in terms of product form and technology stack, Infineon leans more towards "power devices/modules," while Texas Instruments is more focused on "analog ICs (signal chain)." Infineon's "analog/power" focus is closer to core power electronics components: its "Power" analog chip portfolio emphasizes a full spectrum of Si/SiC/GaN, covering MOSFETs, IGBTs, power modules, drivers, protection, and various power conversion solutions. In contrast, Texas Instruments focuses on a "broad-spectrum analog IC (power management + signal chain) + embedded" analog/power chip product platform, with particular strength in the "signal chain + board-level power management" within the analog domain.
The robust earnings from analog chip majors Texas Instruments and STMicroelectronics, their positive outlooks for AI data center-related revenue prospects, and the latest strong performance data disclosed by Infineon indicate that the market-anticipated "strong recovery in analog chip demand driven by the vigorous construction of AI data centers" is unfolding in the chip industry. The seemingly "endless" chip demand from AI training and inference under the unprecedented AI wave is successfully transferring from AI chips and memory chips to the analog chip segment, powerfully driving the earnings of analog chip leaders like Texas Instruments and Infineon towards a robust recovery trajectory.
Texas Instruments' latest optimistic outlook range indicates that major customers have fully digested the massive inventory backlog of analog chips accumulated during the pandemic and have begun placing large-scale orders again—with the core driver primarily being orders for AI data center analog chip business. Texas Instruments CEO Haviv Ilan told analysts on the earnings call that orders grew significantly in the fourth quarter, especially with the strongest growth coming from AI data centers. "The market has been tight; we just need to see how it plays out," Ilan said, citing a 70% revenue growth for Texas Instruments' data center business unit in the quarter ending December.
The chip demand frenzy fueled by AI is spilling over from "computing power chips themselves (GPU/ASIC/HBM)" to the broader "power and signal chain (power + analog/mixed-signal)," and the intensity of this spillover is accelerating significantly. Infineon's recent disclosure of raising its investment plan for this fiscal year from about €2.2 billion to approximately €2.7 billion, and projecting AI data center-related revenue to grow from about €1.5 billion to €2.5 billion (by 2027), is fundamentally based on the logic that AI data center demand provides a powerful "tailwind cycle" during a weak automotive cycle.
Concurrently, Texas Instruments provided a stronger-than-expected Q1 outlook, explicitly listing demand from AI data center investments as one of the driving factors, and the market interprets these figures as "the analog chain beginning to reap the super dividends of AI infrastructure." The underlying engineering logic for analog chips riding the wave of frantic AI computing infrastructure construction is straightforward: AI training/inference systems push "power per cabinet/per rack" to new historical levels, forcing power architecture upgrades (e.g., from 48V to higher voltage HVDC), leading to a "non-linear increase" in the semiconductor content of power devices and power management.
The OCP has publicly indicated that AI rack power will "soon exceed 500kW," and Nvidia is also advancing high-voltage DC architectures for "AI factories," targeting rack scales from 100kW to greater than 1MW. Increasing power consumption doesn't just mean "spending more money on a few more MOSFETs"; it brings about a stacking of components across the entire chain: AC/DC and DC/DC efficiency and thermal design constraints become stricter, multi-stage conversion from 48V (or higher voltage) to point-of-load (<1V) becomes more complex, and GPU/CPU transient currents become steeper—this significantly increases the usage and specification requirements for segments like power stages (FETs/power modules/drivers), multi-phase controllers, hot-swap/eFuses, isolation and current/voltage sensing, clocks, and high-speed signal conditioning.
Infineon is capturing more of the "hardcore power-side increment" (power semiconductors and power solutions required for data center power supplies, power distribution, and board-level conversion). Therefore, amidst strong analog product demand from AI training/inference and weak automotive markets, it emphasizes a strategy of "data center pull, increased investment, and expanded analog chip component capacity." In contrast, Texas Instruments is capturing more of the "board-level power management + signal chain" segment. Texas Instruments publicly breaks down key components for large-scale AI data center computing architectures into combinations "along the power path," such as multi-phase controllers/power stages/point-of-load converters, and hot-swap control, and offers solutions like hot-swap eFuses for 48V architectures, essentially collecting revenue "per watt and per phase" on AI servers/switches/accelerator cards.
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