AI frenzy sweeps through simulated chips! Infineon ramps up data center investments, targeting "AI revenue tenfold growth"

Headquartered in Germany, Infineon Technologies AG, one of the world’s largest semiconductor manufacturers specializing in analog chips, announced strong quarterly earnings and future outlook on Wednesday. In their guidance statement, Infineon’s management indicated plans to increase investments in technology and capacity targeting hyperscale AI data centers, aiming to achieve revenue growth driven by the exponential increase in global enterprise demand for AI computing solutions. Currently, Infineon plans to invest approximately 2.7 billion euros (about $3.2 billion), exceeding previous estimates and the consensus forecast of around 2.2 billion euros.

On Wednesday, Infineon stated that the overall revenue in the data center segment could grow from approximately 1.5 billion euros—about 10% of total revenue—during the current fiscal year to at least 2.5 billion euros by 2027.

“That would mean a tenfold increase in our AI data center-related sales in just three years,” said Jochen Hanebeck, CEO of Infineon, during the earnings call on Wednesday. Benefiting from strong performance and optimistic outlooks, Infineon’s stock price rose as much as 4.2% at the Frankfurt Stock Exchange opening.

This latest strong performance and outlook further reinforce the recovery trajectory of analog chip demand led by Texas Instruments, STMicroelectronics, and NXP—driven by the rapid expansion of AI data center construction led by tech giants like Google, Microsoft, and Meta. Notably, the robust results of Texas Instruments and Infineon, along with TI’s stock reaching new highs amid global market turbulence, highlight that the unprecedented AI wave is creating insatiable demand for chips related to AI training and inference—demand that is smoothly passing from AI and storage chips to analog chips, thereby driving the recovery of industry leaders like Texas Instruments, Analog Devices, Infineon, and NXP.

In terms of overall revenue, Infineon reported total revenue of approximately 3.66 billion euros for the first quarter of fiscal year 2026 ending December 31, up 7% year-over-year, slightly above the analyst consensus of about 3.62 billion euros. Adjusted operating margin was approximately 17.9%, higher than the 16.8% expected by analysts and recently upwardly revised. The company’s long-weak automotive business revenue also slightly exceeded analyst expectations, reaching about 1.8 billion euros.

Regarding other key performance indicators, Infineon’s first-quarter operating profit was about 256 million euros, up roughly 5% year-over-year, slightly above analyst expectations; adjusted earnings per share for the quarter were approximately 0.35 euros, compared to a strong recovery of 0.33 euros in the same period last year, also surpassing analyst estimates.

The company cited CEO comments in its statement: “In a relatively subdued market environment, the demand generated by AI data centers is very active, providing us with an extremely strong tailwind cycle.”

The rising demand for AI data centers is helping Infineon counteract the long-term weakness in its automotive chip business—its largest segment, accounting for about half of total sales, which has been declining since late 2022. Investors have been awaiting a recovery in these more mature chip segments, which have experienced multiple quarters of significant revenue decline driven by prolonged weak demand, especially as automotive chip customers digest inventories built during the COVID-19 pandemic supply shortages.

In November last year, Infineon’s management indicated that sales related to data centers in 2026 would be double those of 2025, after tripling growth the previous year.

Infineon’s Results Reinforce the Global Recovery of Analog Chip Demand

To further diversify its chip business, Infineon announced on Tuesday evening that it agreed to acquire AMS Osram’s automotive, industrial, and medical sensor business for €673 million in cash. These sensors detect and convert signals such as motion and sound into data, used in vehicles, health trackers, and Infineon’s future growth engines—humanoid robots. The transaction will be financed through new debt and is expected to generate approximately €230 million in sales during the current calendar year.

Regarding market expectations, management indicated that current revenue is expected to be around €3.8 billion, slightly above the analyst consensus range, further strengthening the recovery trajectory of analog chip demand led by giants like Texas Instruments.

Infineon expects an adjusted operating margin for the current quarter in the high-single to low-double digits, around 15% to 20%, consistent with the 17.5% forecasted by analysts. The company reaffirmed its outlook from November last year: achieving “moderate revenue growth” for the fiscal year ending September 2026.

Senior Citi analyst Andrew Gardiner and others commented on Infineon’s earnings: “The cyclical recovery is evident in Infineon’s results, but compared to US-based peers like Nvidia, Broadcom, and Micron, the pace is slower and varies by end market. For analog chip manufacturers like Infineon, the clearer growth prospects related to AI are undoubtedly a long-term positive.”

Infineon CFO Sven Schneider stated that the “huge growth potential” of analog chips serving AI data centers is “rising quarter by quarter,” and “one of the largest growth drivers in the company’s history,” during the earnings call.

Both Infineon and Texas Instruments, the world’s largest analog chip maker, share a “power/analog” chip DNA, with their businesses primarily focused on essential analog and power components for data centers, industrial, and automotive applications. The rising power consumption in AI data centers increases demand for power conversion, power management, monitoring, and driving devices. Recently, both companies have publicly emphasized that data center and AI-related demand is driving growth in their analog segments.

In terms of product types and technology stacks, Infineon mainly focuses on “power devices/modules,” while Texas Instruments emphasizes “analog ICs (signal chains).” Infineon’s “analog/power” products are closer to core power electronics, covering Si/SiC/GaN full-spectrum devices, including MOSFETs, IGBTs, power modules, drivers, protection, and power conversion solutions. In contrast, TI’s platform centers on “broad-spectrum analog ICs (power management + signal chain)” and embedded solutions, with particular strength in “signal chain + board-level power management.”

The “chip demand frenzy” driven by AI infrastructure is finally spreading from AI chips and storage chips to the analog chip segment.

The strong performance of Texas Instruments, STMicroelectronics, and the optimistic outlook for AI data center revenue, along with Infineon’s latest results, indicate that the market’s expectation of “robust recovery driven by AI data center construction” is unfolding in the chip industry. Under this unprecedented AI wave, the insatiable demand for chips for AI training and inference is smoothly passing from AI and storage chips to analog chips, further boosting the performance recovery of industry leaders like TI and Infineon.

Texas Instruments’ latest optimistic outlook suggests that major customers have fully digested the backlog of analog chips accumulated during the COVID-19 pandemic and are now placing large new orders—primarily driven by AI data center analog chip demand. TI CEO Haviv Ilan stated during the earnings call that orders in Q4 increased significantly, especially from AI data centers, with “market tightness” evident, and they are watching the results closely. Ilan also noted that TI’s data center revenue in Q4 grew 70%.

The chip demand surge from AI is spilling over from “compute power chips (GPU/ASIC/HBM)” to a broader “power and signal chain (power + analog/mixed-signal),” with the spillover accelerating. Infineon has increased its investment plan for this fiscal year from about €2.2 billion to approximately €2.7 billion, and expects AI data center-related revenue to rise from about €1.5 billion to €2.5 billion by 2027. The core logic is that AI data center demand provides a strong “tailwind” during the weak automotive cycle. Simultaneously, Texas Instruments provided a better-than-expected Q1 outlook, explicitly citing AI data center investments as a growth driver. The market interprets this as the “analog chain beginning to benefit from AI infrastructure super dividends.”

The underlying engineering logic of the “chip demand frenzy” fueled by AI infrastructure is straightforward: AI training/inference systems push “power consumption per rack” to new heights, forcing upgrades in power architectures (from 48V to higher HVDC), which results in nonlinear increases in power semiconductor and power management content.

OCP has publicly indicated that AI rack power will soon exceed 500kW, and Nvidia is promoting high-voltage DC architectures for “AI factories,” targeting rack levels from 100kW to over 1MW. Rising power demands mean more than just “spending on MOSFETs”: they lead to stacking devices across the entire chain—AC/DC and DC/DC efficiency and thermal design become more critical, multi-stage conversions from 48V (or higher) to sub-1V loads become more complex, and transient currents in GPUs/CPUs increase sharply. This significantly raises the requirements for power devices (FETs, power modules, drivers), multi-phase controllers, hot-swappable/ electronic fuses, isolation and current/voltage sensing, clocking, and high-speed signal conditioning.

Infineon’s focus on “power-side core increments” (power semiconductors and power solutions for data center power, distribution, and board-level conversion) positions it to benefit from the strong analog product demand driven by AI training and inference, especially in a weak automotive cycle environment, emphasizing “data center-driven, increased investment, and higher analog chip component capacity.”

In contrast, Texas Instruments’ strength lies in “board-level power management + signal chain”: TI publicly breaks down key components of large-scale AI data center architectures into multi-phase controllers, power stages, point-of-load converters, and hot-swappable eFuses along the power path, offering solutions for 48V architectures—essentially “rent-by-watt and by-phase” on AI servers, switches, and accelerators.