Chips & Compute

Applied Materials to Double Tool Output by 2028 on AI Chip Demand

Applied Materials posted record Q4 revenue of $10.41 billion, up 53%, and said it will double systems output by 2028 as AI chip demand outruns cleanroom capacity.

Applied Materials Is Building to Double Its Tool Output by 2028 as AI Chip Demand Outruns Supply
Applied Materials Is Building to Double Its Tool Output by 2028 as AI Chip Demand Outruns SupplyVo Huyen / unsplash
By Marcus Bennett6 min read

Why it matters

  • Applied Materials reported record Q4 revenue of $10.41 billion, up 53% year over year, and guided to $11.1 billion for the current quarter.
  • CFO Brice Hill said Applied is investing to double systems output from Q4'26 levels by 2028 and more than double manufacturing and lab capacity by 2030.
  • CEO Gary Dickerson expects wafer fab equipment demand to rise more than 30% in 2027, with more than 20 fab ramps tracked for that year.
  • Cloud capex is expected to increase more than 50% in 2027 to well over a trillion dollars, Hill said.
  • Fiscal 2026 revenue reached a record $34.45 billion, up 21%.

Applied Materials reported the largest dollar revenue growth in its history on Thursday: record fiscal fourth-quarter revenue of $10.41 billion, up 53% from a year earlier, and a forecast of $11.1 billion, plus or minus $500 million, for the current quarter. Both numbers beat Wall Street's expectations, and executives said AI chip demand is now running so far ahead of supply that cleanroom space has become the constraint on the entire industry's expansion.

The results land at a moment when AI infrastructure spending is escalating across the supply chain. Applied sells the deposition, etch, polishing and inspection tools that chipmakers use to build AI processors and memory, so its order book is an early read on how much the industry plans to spend on new fabrication capacity (fabs, the plants where chips are made). Its guidance and commentary signal that the buildout now extends years into the future.

What did Applied Materials report?

The headline numbers, for the quarter and the fiscal year ended Oct. 25, according to the company's press release:

  • Revenue of $10.41 billion for fiscal Q4, up 53% year over year, against analyst expectations of $10.30 billion.
  • Non-GAAP earnings of $4.16 per share, up 92%, versus the $4.06 analysts expected.
  • Non-GAAP gross margin of 50.6%.
  • Full fiscal-year revenue of $34.45 billion, up 21% and a record.
  • Current-quarter guidance of $11.1 billion, plus or minus $500 million, above the $10.85 billion analysts expected, according to Quartz, citing The Wall Street Journal.

Chief Executive Gary Dickerson framed the quarter within a structural supply shortage rather than a cyclical spike. "Demand for advanced semiconductors remains much higher than supply, and multi-year investments in new fab capacity are needed for the industry to close this supply-demand gap," Dickerson said on Thursday's earnings call, according to the company's published remarks. He expects wafer fab equipment demand to rise more than 30% in 2027.

Which businesses drove the growth?

Memory and advanced packaging carried the quarter. Semiconductor Systems, Applied's equipment business, brought in $8 billion, up 64%, with record sales in Korea and Taiwan.

The mix shifted toward memory. DRAM, the type of memory used in AI systems, made up 33% of that segment's revenue, up from 28% a year earlier, while foundry and logic slipped to 58% from 66%. Foundry and logic refers to contract chip manufacturing and custom processor design.

Applied expects the shift to accelerate. The company forecasts advanced-packaging revenue to rise about 90% and inspection and metrology revenue to grow more than 50% in its calendar 2026, a period it defines as the second quarter of fiscal 2026 through the first quarter of fiscal 2027. Advanced packaging stacks and connects chip components in ways that speed up AI workloads; inspection and metrology tools verify chip quality during manufacturing.

Why is cleanroom capacity the bottleneck?

The limit on chip supply is now physical rather than financial. "Over the medium term, cleanroom capacity remains a gating factor for how much equipment the industry can consume," Chief Financial Officer Brice Hill said. Cleanrooms are the contaminant-controlled environments where chipmaking tools operate, and building them takes years.

The scale of the pipeline is unusual. Hill said Applied is tracking more than 20 fab ramps and line expansions in 2027 alone, and that for the third consecutive quarter it added more than 10 major fab and expansion projects to its tracker. Many of those projects are not expected to come online until 2029 and 2030.

Customers are adjusting their ordering behavior accordingly. Dickerson said the company's largest customers now provide rolling eight-quarter forecasts and place orders earlier than before. He also said he recently met with more than 250 senior executives from key suppliers to align manufacturing capacity across the chain.

How much is Applied investing to expand?

Hill put the expansion target in explicit terms. The company is "investing to be able to double our systems output from Q4'26 levels by 2028 and more than double our manufacturing and lab capacity by 2030," he said.

The demand signal behind that investment is cloud spending. Cloud capital expenditure, Hill said, "is expected to increase more than 50% in 2027 to well over a trillion dollars." That figure anchors Applied's expectation that equipment demand will keep climbing through the end of the decade.

Other signals corroborate it. Amazon said last month that it plans to spend even more on infrastructure in 2027 than it is spending now, and customers of lithography supplier ASML, whose machines pattern chips at the smallest scales, have been eyeing orders as far out as 2030. The pattern is consistent across the tool chain: buyers are committing years ahead because capacity, not money, is the binding constraint.

How does Applied use AI internally?

Applied is not only a supplier to the AI industry; it is a heavy AI adopter in its own operations. Hill disclosed that more than 80% of Applied's employees use tools including Microsoft Copilot and Anthropic's Claude, and that all of its software developers use AI with an average productivity gain of more than 40%. Monthly token consumption, a measure of how much text the company's workforce feeds through AI models, grew more than 50 times this year.

Those figures make Applied a case study in AI-driven productivity inside a capital-intensive manufacturer, and they tie the company's own efficiency gains to the same demand wave that is filling its order book.

What about shareholders and partnerships?

Applied returned $2.42 billion to shareholders in the quarter, including $2 billion in share buybacks. Hill called that the largest quarterly repurchase in more than eight years. The company has $10.8 billion remaining under its buyback authorization.

Its research ecosystem is also expanding. Since its last report, Intel, Kioxia, Besi and UCLA have joined Applied's EPIC Center research facility in Silicon Valley, bringing announced partnerships to 15. Applied also agreed to raise its stake in Besi, a Dutch assembly-equipment maker, to about 20%.

What does the current quarter look like?

The current quarter runs 14 weeks, one week longer than a standard quarter, which Hill said helps services revenue. Applied expects Semiconductor Systems revenue of about $8.7 billion, up 69% from a year earlier, and it expects its first $2 billion quarter in Applied Global Services, its services business.

Those projections, combined with the 30% wafer fab equipment demand growth Dickerson expects in 2027, indicate Applied does not see the AI capacity race peaking soon. The company has now committed capital toward doubling systems output by 2028 and beyond doubling manufacturing and lab capacity by 2030, which means the supply-demand gap in advanced chips, in Applied's own assessment, will take most of the decade to close.

Source: webpronews.com

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Senior reporter covering companies, deals and strategy in artificial intelligence and machine learning at AI In Context.

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