
Analog Devices has completed its acquisition of Empower Semiconductor for $1.5 billion(約2400億円), a deal aimed at addressing power delivery challenges in AI infrastructure.
Empower's technology is designed to improve efficiency and compute density for AI processors, which the company identifies as energy-constrained systems.
The acquisition strengthens Analog Devices' foothold in the growing AI power delivery market.
What happened
Analog Devices has completed its acquisition of Empower Semiconductor. The all-cash deal, valued at $1.5 billion(約2400億円), was announced on May 19 and is now finalized.
Why it matters
Empower's technology targets energy bottlenecks in AI infrastructure, aiming to improve efficiency, performance, and compute density for AI processors. This acquisition strengthens Analog Devices' position as a system-level grid-to-core power partner across the AI ecosystem and expands its total addressable market in AI compute power delivery.
What to watch
CEO Vincent Roche stated that AI infrastructure is reshaping power delivery, with energy now one of the most persistent constraints to scaling next-generation systems. The combined capabilities are intended to help customers rearchitect their power systems and achieve the compute densities next-generation AI demands.
Ask the AI about this article →
Analog Devices announced the acquisition of Empower Semiconductor on May 19 and has now completed the transaction. According to CEO Vincent Roche, the deal addresses a fundamental challenge in modern AI systems: power delivery at scale. As AI infrastructure grows, energy constraints have become a persistent limitation on compute density and system performance, and Empower's technology is positioned to unlock efficiency gains in this area.
The acquisition expands Analog Devices' capabilities as a system-level power partner. By combining Analog Devices' existing technology and scale with Empower's breakthrough power-delivery solutions, the company intends to help customers redesign their power architectures to support next-generation AI compute demands. This move reflects the broader industry shift toward treating power delivery as a critical bottleneck in AI infrastructure expansion, not merely a supporting component.
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