The Pacific Securities Co., Ltd. released a research report indicating that Advanced Micro Devices' data center business has become the core growth engine, benefiting from the surge in AI computing demand. The increase in the proportion of high-margin products has driven an overall enhancement in profitability. The company's deep collaboration with leading clients such as Meta has led to continuous upward revisions in the market potential for server CPUs and AI chips. AI inference and agent applications are reshaping the computing power structure, elevating the role of CPUs. The main points of The Pacific Securities Co., Ltd. are as follows:
Advanced Micro Devices released its fiscal year 2026 first-quarter financial results, reporting quarterly revenue of $10.25 billion, a year-over-year increase of 37.9%, with sequential performance largely flat. The gross margin was 52.8%, up 2.6 percentage points year-over-year, while net profit reached $1.38 billion, a 95.1% increase compared to the same period last year.
AI-driven data center business growth propelled strong performance. The company's operations are divided into three segments: data center, client, and gaming. This quarter, data center revenue reached $5.78 billion, a 57.2% year-over-year increase, accounting for 56.3% of total revenue. This growth was primarily driven by strong demand for the fifth-generation EPYC server processors and the Instinct MI350 series AI accelerator chips, supported by large-scale procurement from cloud computing giants and AI-related enterprises. Client segment revenue was $2.89 billion, up 25.8% year-over-year, benefiting from increased sales and average selling prices of Ryzen series processors. Gaming revenue reached $720 million, an 11.3% year-over-year increase, as recovering demand for discrete graphics cards offset a slight decline in semi-custom business. Embedded segment revenue was $870 million, a 6.1% year-over-year increase, accounting for 8.5% of total revenue, driven by steady recovery in industrial, automotive, and communication market demand.
The year-over-year improvement in gross margin is primarily attributed to the increased proportion of high-margin data center AI chips and server processors, reflecting an ongoing shift toward more premium, high-value-added product portfolios. On the expense side, rational expansion continued, with R&D expenses reaching $2.397 billion, a 38.7% year-over-year increase, focused on investments in AI accelerators, next-generation CPU/GPU architectures, and advanced process development. Sales, general, and administrative expenses amounted to $1.253 billion, up 41.4% year-over-year, supporting global market and customer expansion. The growth in expenses aligns with revenue growth, maintaining stable operational efficiency.
Focus on AI computing infrastructure, achieving breakthroughs in both products and customers. This quarter, Advanced Micro Devices secured a deep collaboration with Meta, including a large-scale GPU procurement order, with commitments for mass deployment of the MI450 series custom chips and sixth-generation EPYC processors. The server CPU market continues to expand, with the company significantly raising its long-term market outlook for server CPUs. AI inference and agent applications are reshaping the computing power structure, further elevating the importance of CPUs.
Industry growth momentum continues, with the company guiding for strong performance. Advanced Micro Devices expects fiscal year 2026 second-quarter revenue to be approximately $11.2 billion, representing a year-over-year increase of about 46%, plus or minus $300 million. Non-GAAP gross margin is projected to be around 56%. Server CPU revenue is expected to show strong year-over-year growth, with this robust momentum likely to continue. As the company expands supply to meet incremental market demand, growth in the server business is anticipated to accelerate significantly. Industry client engagement with data center GPUs continues to rise, with demand from leading customers exceeding earlier expectations, and large-scale deployment project pipelines expanding further.
Risk factors include slower-than-expected progress in the AI industry and potential delays in capacity expansion.
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