Applied Materials Raises Outlook as AI Infrastructure Spending Accelerates

Applied Materials raised its revenue outlook for the current quarter after reporting record second-quarter results, as AI infrastructure spending continued increasing demand for semiconductor manufacturing equipment. The California-based semiconductor equipment company projected third-quarter revenue of about $8.95 billion, plus or minus $500 million, above Wall Street estimates of $8.09 billion, according to analysts tracked by the London Stock Exchange Group. The company reported second-quarter revenue of $7.91 billion for the quarter ending April 26, up 11% year over year. Net income rose 31% to $2.8 billion. Gary Dickerson, President and CEO of Applied Materials, said the company now expects its semiconductor equipment business to grow more than 30% during calendar year 2026. “The growth in AI that Applied has been investing for is now in full force,” Brice Hill, Senior Vice President and CFO of Applied Materials, said during the earnings discussion. The results add to growing evidence that AI spending is expanding beyond cloud infrastructure providers and model developers into the semiconductor manufacturing supply chain. Building advanced AI processors requires increasingly complex wafer fabrication, packaging, and testing systems, driving new demand for equipment suppliers. AI-related semiconductor demand has also accelerated long-term fab expansion and procurement activity across the industry, with manufacturers and infrastructure builders increasingly locking in future supply capacity. AI Demand Pushes Semiconductor Manufacturing Expansion Applied Materials is among several semiconductor equipment companies benefiting from hyperscaler and AI infrastructure investment. Earlier this year, ASML raised its 2026 outlook on stronger AI-related semiconductor demand, while Taiwan Semiconductor Manufacturing Company (TSMC) said global semiconductor revenue could reach $1.5 trillion by 2030 as AI deployment expands. Industry group SEMI expects global wafer fabrication equipment spending to rise to about $126 billion in 2026 as AI demand increases investment in advanced manufacturing capacity. Building advanced AI semiconductor capacity remains constrained by multiyear fab construction timelines, extreme ultraviolet (EUV) lithography tool availability, and qualification bottlenecks. Applied Materials said demand remained strongest in advanced foundry and logic manufacturing, where chipmakers are increasing production capacity for AI accelerators and high-bandwidth memory systems. The company’s shares rose nearly 5% in after-hours trading following the earnings release. The stock has gained more than 150% over the past year amid continued investor optimism around AI infrastructure spending. Semiconductor Supply Chain Sees Broader AI Effects The AI infrastructure boom is also affecting networking, memory, and semiconductor testing companies across the broader supply chain. Cisco recently raised its full-year AI infrastructure order forecast to $9 billion after reporting increased demand from hyperscalers for AI networking systems. AI chip production is also reshaping semiconductor testing and validation systems, where manufacturers are integrating GPU-powered real-time analytics directly into production environments. At the same time, supply chain constraints continue emerging across advanced memory and packaging systems used in AI hardware. Reuters reported earlier that demand for high-bandwidth memory chips and advanced packaging capacity has created new bottlenecks across the semiconductor industry. The AI infrastructure buildout has also reshaped GPU cloud economics, with hyperscalers and specialized compute providers competing aggressively for hardware access and capacity.

Applied Materials Raises Outlook as AI Infrastructure Spending Accelerates

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