data center racks with person walking through

The need for highly specialized, sustainable environments

Where data centers have traditionally been designed around CPUs, AI data centers are built around GPUs, which use exponentially more power and require new types of power distribution and cooling. This is fundamentally altering the financial and risk profile of the industry.


2026 is projected to become the year where demand for colocated power will officially outstrip supply.

Data center capacity is projected to outstrip supply from 2027-2030, with annual global demand outpacing supply by as much as 500%.1


up close city building with blue overlay

“We can no longer treat data strategy and physical infrastructure as separate conversations. We are tackling the hardware bottlenecks, component costs, and environmental realities of this storage explosion head-on by breaking down traditional IT silos—uniting asset management with data center capacity to build the scalable, cross-functional architectures required to deliver real business value.”

— IT leader, Financial Services2

man giving a presentation with blue diamonds overlay

The inferencing shift: From training to front-line operations

While the initial AI boom was defined by the massive energy required to train LLMs, the market is entering a more taxing phase, dominated by AI inference.

Unlike training, which can be treated as a periodic capital expense, AI inferencing is a continuous operational cost where every query, agentic workflow, and real-time diagnostic creates both a cost and resource drain.

Fast AI performance requires inferencing close to where customers and employees operate, turning local power grid capacity into a premium commodity.

Cloud and AI construction are moving in opposite directions.

Traditional cloud storage demands massive, sprawling footprints with moderate power draw (5–15 kW per rack). In contrast, AI workloads require extreme, localized density (50–120 kW+ per rack).1

5-15

kW per rack

Traditional cloud storage

50-120+

kW per rack

AI workloads



In terms of critical IT load capacity, AI inference is projected to grow at a 79% CAGR, significantly outpacing AI training’s 25% CAGR over the same period.2



From procurement to strategy: Mastering the 24-month strategic horizon

In the software world, cycles are measured in months and quarters. Data centers are measured in years and growing. Data center cycles used to reflect a 6-to-12-month procurement exercise; this is now at 18–24 months and growing. Organizations that see data centers as operational line items need to treat them as a key part of capital allocation and information and risk management strategies.

As AI puts simultaneous demands on data management, hardware processing, and power availability, it’s time to pull planning cycles forward and move them higher up in the organization. By balancing the needs of information access, governance, and storage with the proactive management of IT assets and infrastructure enterprises can ensure long-term cost predictability and secure what’s needed to become an AI-driven enterprise.

infrastructure readiness ranked as top concern when planning for AI's future graphic

In Iron Mountain’s research infrastructure readiness ranked as top concern when planning for AI's future. When asked to rank the most critical challenges, respondents answered (ranked #1 / ranked in top 3)2

Successfully achieving this depends entirely on locking down data center access before the available runway disappears.

Data center as geopolitical strategy and license to operate

Data centers are an emerging area of legal and geopolitical strategy, as we enter a period of active, aggressive government oversight. With 172 countries having enacted data privacy laws by 2025, according to privacy law researcher Graham Greenleaf, data sovereignty is a non-negotiable business constraint.3 Enterprises must now weigh not just where a server sits, but the nationality of the provider.

A U.S. headquartered data center provider that’s operating in Europe is bound by both European privacy rules (GDPR) and American law (The CLOUD Act). American authorities can compel these providers to disclose data regardless of where it’s physically stored. For global businesses, complying with a U.S. warrant could trigger European fines for unauthorized data transfers. Navigating this conflict requires a data center partner who can offer architectural sovereignty—keeping data legally and technically isolated from foreign interference.

Data center legislation is exploding.

238

U.S. bills in 2025

300+

through April 2026


In 2025 US lawmakers introduced 238 bills targeting data center regulation; through April 2026,
300+ bills have been introduced, a 3.7X increase.4

Future-proofing for the GPU era.

The winners of the AI race won’t just be defined by their models and data, but by their ability to navigate a world where power is an important bottleneck for growth. As we scale AI inference across AI agents and enterprise workflows, companies also need to navigate the supply-demand gap for power.

As bills and regulations continue to target energy use and data sovereignty, companies need to navigate and balance the conflicts that may arise across borders. We see sustainability as irrevocably aligned to this new era, and part of what every organization needs to prioritize as part of this mission critical strategy.

Actions you can take today:

arial view of a highway in a city

Future-proof your infrastructure.

Iron Mountain can help you elevate go-forward infrastructure conversations to secure guaranteed access to the high-performance compute power needed to power AI. We’ve already helped organizations across the world build the physical and digital infrastructure required to scale AI securely, reliably and responsibly.

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When you’re ready to power sustainable innovation.

Our ALM and Data Center experts help you treat clean data like green data. By liquidating data debt and optimizing your infrastructure, we provide a clear path to meeting Net-Zero milestones—turning circularity into a financial strategy that frees up the power and budget required to fuel your future AI clusters without compromising your ESG commitments.

Learn more about Iron Mountain Data Centers

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Sources

1 Structure Research and Iron Mountain Data Centers, “Will AI eat the cloud?” November 2025.

2 Iron Mountain, “The information supercycle: Aligning data, infrastructure, and capital for AI scale,” October 2026.

3 Graham Greenleaf, “172 countries with data privacy laws: Year by year 1973-2025,” Privacy Laws & Business International Report, issue 195, June 2025. Count as of March 2025.

4 MultiState, “Here’s what you need to know about data center policy trends,” November 4, 2025. Lawmakers in all 50 states considered 238 data center-related bills in 2025.

Sources reviewed October 2026.