NTT DATA has released a new report examining whether the world's data center infrastructure can scale quickly enough to support accelerating artificial intelligence adoption.

Developed in collaboration with NTT Global Data Centers and economic consultancy ThoughtLab, Can Data Centers Keep Pace with AI? A Global Data Center Outlook models three scenarios for worldwide data center expansion through 2030. The report projects annual demand growth of 23% to 30% under the most likely scenarios, while warning that constraints related to power availability, equipment supply chains, land access and skilled labor could limit capacity unless addressed through coordinated planning.

"AI demand is accelerating faster than many parts of the underlying infrastructure system can respond," said Doug Adams, CEO and President, NTT Global Data Centers. "The challenge now is not simply scaling capacity, but removing the operational and supply-side constraints that delay deployment and erode the economics of AI investment. This report is intended to help the market move from recognizing the challenges to acting on practical solutions."

According to the report, several factors are emerging as critical barriers to expansion:

• Power availability and grid connections are becoming major constraints in key markets, particularly across the United States and Europe.
• Supply chain bottlenecks involving processors, transformers, switchgear and backup generators are extending project timelines due to limited manufacturing capacity and long lead times.
• Land availability, permitting delays and community opposition are slowing development in high-demand markets.
• Skilled labor shortages in specialized construction trades are increasing project risk and lengthening delivery schedules.

While identifying these challenges, the report also outlines strategies to help expand capacity and improve the efficiency of AI infrastructure investments. Recommendations include:

• Coordinating power and grid planning with utilities early in the development process.
• Building more resilient supply chains through supplier diversification, long-term procurement agreements and standardized equipment specifications.
• Increasing operational efficiency with advanced cooling technologies, liquid and direct-to-chip cooling, workload optimization and AI-enabled data center operations.
• Expanding the use of standardized performance metrics, including Power Usage Effectiveness (PUE) and Water Usage Effectiveness (WUE), to improve planning and investor confidence.
• Strengthening community engagement and site selection strategies to accelerate project approvals while addressing local concerns.

"AI infrastructure demand is no longer a future scenario. It is here now," Adams added. "The organizations that move fastest over the next several years will be those that understand where the real constraints are, act early to mitigate them, and build with efficiency, resilience and long-term value creation in mind."

Source: NTT DATA

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