Why Software Matters as Much as Steel in Hydrogen Hubs

As US hydrogen hubs scale up, artificial intelligence is emerging as a critical tool to cut costs, smooth volatility, and keep production on track

21 Jan 2026

The next phase of the US green hydrogen buildout is being shaped less by the number of projects announced than by how efficiently they operate. As clean hydrogen hubs move closer to commercial reality, developers are turning to artificial intelligence to manage fluctuating power supply, volatile prices and complex equipment loads.

Honeywell is among the industrial groups positioning AI as an operational tool rather than an experimental add-on. The company has launched Honeywell Protonium, an AI-assisted software suite designed to optimise green hydrogen production. It says the aim is to improve efficiency, reduce operating costs and support projects that must run reliably at scale.

The software is planned for deployment by Aternium in connection with the Mid-Atlantic Clean Hydrogen Hub, known as MACH2. The hub model links multiple producers and buyers across a region, increasing the importance of stable and predictable output. Disruptions at a single facility can have wider effects across the network.

US hydrogen hubs are backed by substantial federal support. The Department of Energy has committed about $7bn across seven regional hubs, seeking to accelerate clean hydrogen production, infrastructure and end-use demand. As these projects advance, attention is shifting from construction timelines to operational performance.

Green hydrogen plants face uneven operating conditions. Electricity supply can change hour by hour, while power prices can move sharply. Electrolysers and related equipment are also exposed to stress as output ramps up and down. Honeywell says its AI tools are designed to learn from operating data, allowing plants to adjust in real time, reduce waste and limit downtime.

In its announcement, the company said Protonium is intended to make green hydrogen production more efficient and cost-effective. For the sector, this signals that software and data management may be as important as improvements in electrolyser technology.

Obstacles remain. AI systems rely on high-quality, integrated data, which early-stage hydrogen facilities may lack. Greater connectivity also raises cybersecurity risks.

Even so, the trend is becoming clearer. As hubs such as MACH2 expand, AI-driven optimisation is emerging as part of the competitive toolkit, shaping how the US green hydrogen industry performs once projects move beyond the drawing board.