NTT DATA, in partnership with NTT Global Data Centers and economic consultancy ThoughtLab, has released a new global analysis examining whether the infrastructure required to support the next wave of artificial intelligence can scale fast enough to meet exploding demand.
The report, titled “Can Data Centers Keep Pace with AI? A Global Data Center Outlook,” models three scenarios for global data center expansion through 2030. It finds that while demand is projected to grow between 23% and 30% annually, severe capacity constraints across power, equipment supply chains, land availability, and labor could create a capacity crunch if not addressed through coordinated global action.
Key insights from the report highlight the primary operational bottlenecks facing the industry:
- Grid and Power Constraints: Power availability and grid connections have become decisive constraints in major markets, particularly in the United States and Europe.
- Supply Chain Chokepoints: Processors, transformers, switchgear, and backup generators are emerging as significant bottlenecks, with long lead times and limited manufacturing capacity stalling project fit-outs and energization.
- Siting and Labor Challenges: Rising community opposition and land constraints are delaying regulatory approvals in prime markets, while shortages in specialized construction labor increase execution risks and extend delivery timelines.
To unlock capacity and improve the performance economics of AI infrastructure, the report outlines a strategic roadmap with several core recommendations:
- Proactive Utility Planning: Co-plan power and grid infrastructure early with utilities to align new projects with generation, transmission, storage, and interconnection realities before bottlenecks delay deployment.
- Resilient Procurement: Strengthen supply chains by diversifying vendors, securing long-term procurement agreements, standardizing equipment specifications, and treating long-lead components as strategic priorities rather than late-stage purchasing decisions.
- Efficiency Innovation: Drive innovation through advanced cooling—including liquid and direct-to-chip cooling—workload optimization, and AI-enabled operations to reduce energy and water resource pressure.
- Transparent Benchmarking: Establish consistent use of metrics like power usage effectiveness (PUE) and water usage effectiveness (WUE) to boost planning and investor confidence around efficient capacity expansion.
- Community Engagement: Improve community engagement and siting strategies to accelerate project approvals with clearer public understanding of economic benefits and infrastructure mitigation steps.
“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.”