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Global Semiconductor Revenue Likely To Touch $1.9 Trillion In 2027

OMMCOM NEWS by OMMCOM NEWS
August 25, 2026
in Business, Nation, Science & Tech

New Delhi: Global semiconductor revenue is expected to reach $1.6 trillion in 2026, an increase of 92 per cent from $809 billion in 2025, and is further expected to touch $1.9 trillion in 2027, a report has said.

The report from business and technology insights company Gartner, Inc. said the industry is entering a “fundamentally new phase of growth” driven by sustained investment in AI infrastructure and a stronger‑than‑anticipated memory pricing cycle.

Memory revenue is expected to total $837 billion in 2026 and surpass $1 trillion in 2027. Memory remains the primary contributor to semiconductor industry growth this year and is forecast to account for 54 per cent of total semiconductor revenue, up from 27 per cent in 2025, the report noted.

“Rising AI infrastructure is reshaping investment across the semiconductor ecosystem and redefining the industry’s application mix. The AI data center ecosystem is expected to grow from 36.5 per cent of the semiconductor revenue in 2026 to more than 53 per cent by 2030, underscoring a structural shift in where semiconductor value is created and how demand is evolving across the industry,” said Ben Lee, Director Analyst at Gartner.

The firm forecasted DRAM revenue to increase 246.6 per cent in 2026, while NAND flash revenue to grow 371.9 per cent.

Although additional capacity is expected to enter the market in 2027, supply-demand conditions are projected to remain tight as AI infrastructure deployments continue to increase memory consumption.

“AI infrastructure has fundamentally changed the dynamics of the memory market,” said Shrish Pant, Director Analyst at Gartner.

“While pricing expansion is accelerating growth in 2026, continued AI infrastructure deployments, higher memory content per AI server and sustained demand for high-bandwidth memory (HBM) will support memory revenue growth through 2027 and beyond,” Pant added.

As AI clusters become larger, faster and more power-intensive, they require increasing investment in CPUs, networking silicon, power management, analog devices and optical interconnect technologies.

(IANS)

Tags: Semiconductor
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