Hitachi Energy expands Celonis AI partnership on supply

Hitachi Energy has expanded its collaboration with Celonis to use artificial intelligence across its global operations as part of its AI Nexus transformation programme.

The expanded partnership is intended to improve efficiency, strengthen supply chain resilience and support the delivery of electricity infrastructure as demand for grid equipment rises.

Hitachi Energy is applying Celonis' process intelligence software to operational data from across its business systems. The goal is to give teams a clearer view of bottlenecks, dependencies and potential disruptions in manufacturing and supply chains.

The collaboration also includes Hitachi Digital and uses technology from partners including Databricks and Microsoft. Together, the companies have built an architecture designed to connect digital systems, operational data and AI tools at scale.

Operational focus

At the centre of the arrangement is the Celonis Context Model, which brings together information from across Hitachi Energy's business systems. The operational context is intended to help AI agents and automations identify dependencies, anticipate disruption and recommend actions.

One example is an AI agent that flags supply disruptions before they affect production. According to the companies, the system can identify production-critical materials at risk of delay and suggest steps to protect continuity in factories.

The approach reflects a broader push by industrial groups to link AI applications more closely to day-to-day operations rather than limit them to isolated pilot projects. Manufacturers supplying electricity networks face pressure to increase output, manage complex sourcing networks and cut delivery times as electrification, industrial expansion and AI-linked data centre growth drive demand for equipment.

Hitachi Energy said wider use of AI-driven optimisation should support productivity, efficiency and profitability while helping the company manage a growing order backlog.

Infrastructure demand

The expansion comes as suppliers to the power sector respond to a sharp rise in investment needs across transmission, distribution and related infrastructure. Companies making transformers, substations and grid equipment have been dealing with long lead times, component shortages and capacity constraints as utilities and industry increase spending on network upgrades.

For Hitachi Energy, which employs more than 56,000 people in 60 countries and generates about USD $20 billion in revenue, operational performance has become increasingly important as customers seek faster delivery of critical systems.

Celonis, based in Munich and New York, sells process intelligence software that analyses how work moves through business systems. Its products are used to map workflows, identify inefficiencies and provide context for automation and AI tools.

Urs Dogwiler, Chief Transformation Officer and Chief Lumada Business Officer at Hitachi Energy, said the partnership is intended to make AI useful in practical operating settings. "AI creates the greatest value when it is connected to the reality of how a business operates, and that is a vision we share with Celonis," he said. "Through AI Nexus, we are combining our deep domain expertise with trusted data and AI to transform the way we work. Celonis helps our teams anticipate supply risks, act sooner and improve delivery performance, making AI a practical driver of operational excellence."

Celonis described the collaboration as an example of AI being applied to industrial infrastructure rather than back-office processes alone. "Hitachi Energy is applying AI to one of the defining infrastructure challenges of the electricity era," said Bastian Nominacher, Co-Founder and Co-Chief Executive Officer at Celonis. "By grounding AI in the operational context of Hitachi Energy's processes, we can help teams identify risks sooner, coordinate action across complex workflows and accelerate the delivery of critical infrastructure."

The arrangement highlights how manufacturers are trying to embed AI in procurement, planning and production decisions as they manage more volatile supply networks. The focus is less on consumer-facing applications and more on reducing manual work, improving responsiveness and keeping projects on track in complex industrial operations.

Those aims are particularly relevant in the electricity sector, where delayed equipment can hold up substation upgrades, renewable connections and wider grid expansion. The collaboration is intended to turn advances in AI into measurable industrial performance by combining software tools with the expertise of the people who design, manufacture and deliver critical infrastructure.