Latest NewsNew Report Finds Semiconductors Account for 95% of an AI Data Server Rack’s Value, Encompassing the Full Stack of Chip Technologies

SIA-Deloitte study estimates annual revenue from chips deployed in AI data centers could reach over $1.2 trillion by 2028, a nearly tenfold increase over four years WASHINGTON, June 1, 2026 – The Semiconductor Industry Association (SIA), in partnership with Deloitte, today released a report finding the full range of semiconductor technologies are integral to artificial intelligence (AI), accounting for a significant share of the value of AI infrastructure and presenting a massive market opportunity in the years ahead.

The report, titled “Powering AI: The Semiconductor Ecosystem at the Foundation of Data Centers,” offers a unique, inside-out look at the heart of AI infrastructure by conducting a virtual teardown of a state-of-the-art AI data server rack, the foundational unit of centralized AI infrastructure.

As policymakers advance efforts to promote U.S. leadership in AI – including the Trump Administration’s Pax Silica Initiative and its AI Exports Program – the new report finds chips account for more than 95% of a leading AI server rack’s content value and more than 50% of the total capital expenditures required for building and operating an AI data center.

The study also details how AI requires the full range of semiconductor technologies, including logic, memory, and analog and foundational chips. Additionally, the report projects annual revenue for semiconductors used in AI data centers could reach $1.2 trillion by 2028.

This represents a nearly tenfold increase over the last four years and surpasses total global semiconductor sales from 2025 – across all end uses – by more than 50%. “The future of AI will be determined by the full array of semiconductor technologies that power it,” said John Neuffer, SIA president and CEO.

“To ensure global AI adoption is built on American chips, we need government policies that promote access to global markets and strengthen U.S. competitiveness. We stand ready to work with policymakers to ensure American semiconductor technology remains the engine of AI innovation for many years to come.”

Other key findings from the report: AI data centers need huge amounts of compute, storage and memory bandwidth, power distribution, and networking capabilities, all provided by the full stack of chip technologies. In total, a single AI server rack contains over 4,500 packaged chips.

These include: Advanced logic chips, such as AI accelerators, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), central processing units (CPUs), data processing units (DPUs), and networking chips. Memory, such as high-bandwidth memory (HBM), both dynamic and static random-access memory (DRAM and SRAM), and non-volatile flash memory (NAND).

Analog and foundational chips, such as power chips, transceivers, controllers, and sensors. Advanced logic chips, such as AI accelerators, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), central processing units (CPUs), data processing units (DPUs), and networking chips.

Memory, such as high-bandwidth memory (HBM), both dynamic and static random-access memory (DRAM and SRAM), and non-volatile flash memory (NAND). Analog and foundational chips, such as power chips, transceivers, controllers, and sensors.

To meet global demand for new AI applications, government and industry will invest over $4 trillion in new data center infrastructure through 2028, of which up to $2.8 trillion will be spent on semiconductors.

The report also analyzes future market trends in the AI data center landscape, particularly with a focus on the rapid changes to AI in the coming years that will pose both challenges and opportunities for the semiconductor industry. As AI continues to evolve rapidly, global competition for leadership will continue to intensify and technological changes will necessitate continued innovation. ###