The Japanese group plans to mass-produce data-centre battery cells in Kansas by fiscal 2028, redirecting a large slice of its AI infrastructure investment toward storage.

The companies that built batteries for electric cars are discovering a new and hungrier customer: the data centre.

Panasonic plans to localise production of data-centre battery cells in the United States, its energy unit’s chief executive has said, building the cells at a plant in Kansas rather than shipping them in, as the Japanese group chases a market that barely existed a few years ago.

Mass production at the Kansas site is scheduled for the financial year ending March 2029, which Panasonic counts as fiscal 2028.

The plant gives the company a domestic base to supply American data-centre operators directly, a meaningful advantage at a moment when tariffs, supply-chain anxiety, and the sheer speed of AI build-out have made onshore manufacturing a competitive asset rather than a cost to be minimised.

The money behind the move is substantial. Panasonic is directing about 350 billion yen, roughly $2.18 billion, of a previously announced 500 billion yen AI infrastructure investment over fiscal 2026 to 2028 to its Energy unit, the division that also supplies Tesla, with the remaining 150 billion yen going to its Industry segment.

The split tells you where the company thinks the growth is: the battery business that grew up around electric vehicles is being retooled to feed the server hall.

The ambition is sized accordingly. Panasonic Energy chief executive Kazuo Tadanobu described the unit’s 950 billion yen sales target for data-centre-related energy storage in fiscal 2028 as a “minimum commitment,” with the business aiming to push sales past 1 trillion yen.

For a target to be framed as a floor rather than a goal is a sign of how quickly the company expects demand to climb.

The logic is grounded in how modern data centres actually run. The facilities training and serving AI models draw enormous, spiky loads, and they cannot tolerate even a flicker of interruption, which makes large-scale battery storage essential for smoothing supply, bridging outages, and managing the gap between what the grid can deliver and what the racks demand at any given instant. As AI compute scales, the storage attached to it scales with it.

The cells these facilities need are also a different specification from the ones that go into cars, tuned for grid-style duty cycles rather than the range and weight constraints of a vehicle, which is part of why an established battery maker still has to build dedicated capacity rather than simply repurpose its existing lines.

That demand is already straining the systems around it. The build-out has pushed electricity grids to their limits, with operators from Denmark pausing new connections to China wrestling with how to match clean power to data-centre load, a backdrop that makes on-site storage less of a luxury than a requirement.

Batteries are becoming part of the basic plumbing of AI, not an optional extra bolted on at the end.

Panasonic is not moving into an empty field. Chinese battery giants including CATL are racing into the same data-centre storage market, and the competition runs alongside the broader contest over the silicon inside those facilities, where Chinese firms are pushing domestic alternatives to Nvidia at speed.

The energy layer of the AI stack is becoming as contested as the compute layer.

The US plant is one node in a wider network. Panasonic Energy also plans a third plant in Mexico, with mass production likewise targeted for fiscal 2028, giving it North American capacity on both sides of the border.

The company has not detailed the Kansas site’s output volumes or named the data-centre customers it expects to supply, leaving the commercial specifics to emerge as production approaches.

What is clear is the direction: a battery maker that bet its future on cars is now placing a second bet, on the machines learning to think.