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标题: "The Corrosion Blind Spot in the AI Buildout"
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---

[

Insight and analysis on the data center space from industry thought leaders.

](https://www.datacenterknowledge.com/program/industry-perspectives)

AI data centers' massive capital investments are at risk from corrosion, which begins during construction – not operations – yet preservation is rarely included in project governance or early planning.

Getty Images

The global race to build artificial intelligence infrastructure represents one of the largest capital investment cycles in modern history. Technology companies are investing unprecedented sums in AI infrastructure and new data centers as demand for advanced computing capacity continues to accelerate. Every hyperscale campus represents an enormous investment in computing hardware, electrical infrastructure, cooling systems, and supporting utilities.

Despite this unprecedented growth, one important aspect of asset reliability often receives little attention during project planning: corrosion.

Much of the industry's attention has understandably focused on power availability, [liquid cooling](https://www.datacenterknowledge.com/cooling/liquid-cooling-options-rdhx-direct-to-chip-immersion), rack density, and deployment speed. These are critical challenges, but they have also shifted attention away from another factor that directly affects long-term reliability. Corrosion rarely creates immediate problems during construction, making it easy to overlook until equipment is commissioned or placed into service.

Corrosion is still widely treated as a maintenance issue. In reality, it often begins months before a facility becomes operational as equipment moves through manufacturing, transportation, storage, and construction. For facilities expected to operate continuously while supporting billions of dollars in computing infrastructure, preservation decisions made during these early phases can have lasting consequences for reliability and asset life.

## A Growing Challenge for Next-Generation Data Centers

Industry studies estimate that the cost of corrosion is approximately 3.4% of global GDP each year, much of it preventable through established corrosion management and preservation practices. While data centers have historically faced relatively limited exposure to corrosion, the rapid adoption of liquid cooling is changing that equation.

High-density AI infrastructure introduces extensive liquid-cooled equipment, cooling distribution systems, heat exchangers, pumps, valves, and piping networks that combine multiple metals and increasingly complex [water chemistry](https://www.datacenterknowledge.com/sustainability/4-strategies-for-eliminating-data-center-water-pollution). As a result, corrosion can reduce cooling efficiency, delay commissioning, shorten equipment life, and affect the reliability of mission-critical computing infrastructure.

## Corrosion Is Often a Governance Issue, Not a Technology Issue

Most large construction projects include well-defined governance processes for quality assurance, commissioning, safety, and risk management. Preservation, however, is often absent from those same governance frameworks. As equipment moves through manufacturing, transportation, storage, installation, and commissioning, responsibility shifts between manufacturers, logistics providers, contractors, and owners.

As schedules shift and equipment remains idle longer than originally planned, preservation activities may become inconsistent or overlooked altogether. Without clearly defined ownership as equipment moves between manufacturers, logistics providers, contractors, and owners, corrosion can begin long before it becomes visible. By the time it is discovered, the opportunity to prevent it has often passed.

## Other Asset-Intensive Industries Recognized This Challenge Decades Ago

Oil and gas, petrochemical, power generation, marine, and heavy industrial manufacturers routinely establish preservation requirements before purchasing equipment. Preservation activities are documented throughout construction, verified during commissioning, and incorporated into project quality programs because maintaining equipment condition is recognized as part of protecting the overall capital investment.

AI infrastructure is reaching a similar level of complexity and capital intensity, making many of these established practices increasingly relevant.

## Preservation Begins During Design

The most effective preservation strategy starts long before construction begins.

During project planning, designers can evaluate material compatibility, identify potential risks of galvanic corrosion, specify coolant chemistry, minimize stagnant flow areas, and establish preservation requirements for equipment that may remain in storage for extended periods.

Early planning also allows preservation requirements to be incorporated into procurement documents and construction specifications. When preservation expectations are documented from the outset, contractors, suppliers, and commissioning teams have a common standard to follow rather than making decisions independently as project schedules evolve.

Organizations may choose to develop internal preservation standards, incorporate requirements into engineering specifications, or engage independent specialists to help establish procedures and verify asset condition throughout construction. Regardless of the approach, clearly defined responsibilities and documented inspection points improve consistency while reducing project risk.

## Preservation Across the Project Lifecycle

Preservation should extend across manufacturing, transportation, storage, commissioning, and operations. Equipment often spends months moving between suppliers, ports, laydown yards, warehouses, and partially completed facilities before entering service, creating repeated opportunities for corrosion. Whether protecting cooling systems, electrical infrastructure, computing equipment, or spare assets, the objective remains the same: maintaining equipment condition until reliable operation begins.

![chart illustrating corrosion management in AI data center lifecycle ](https://eu-images.contentstack.com/v3/assets/blt8eb3cdfc1fce5194/bltbb527cc80d9e1440/6a99ed04e564e77ff01d4f44/AI_Data_Center_Project_Lifecycle_Corrosion_Management_Chart.png?width=1400&auto=webp&quality=80&disable=upscale "chart illustrating corrosion management in AI data center lifecycle ")

(Image: ZERUST Integrity Solutions)

## Looking Beyond Maintenance

As AI data centers continue to [scale up in power density](https://www.datacenterknowledge.com/ai-data-centers/ai-rack-density-s-real-limits-power-cooling-failure-risk) and capital investment, preservation should be viewed as part of overall asset management rather than simply another maintenance activity.

The question is no longer whether corrosion will occur but whether preservation has been considered early enough to prevent it. Organizations that incorporate preservation planning into design, procurement, construction, and commissioning will be better positioned to protect capital investments and support the long-term reliability expected from modern AI infrastructure.

## About the Authors

ZERUST Integrity Solutions

Gautam Ramdas is Vice President of Global Market Development for ZERUST Integrity Solutions®, a division of Northern Technologies International Corporation (NASDAQ: NTIC), with more than 25 years of experience in corrosion management, asset preservation, and critical infrastructure reliability.