The AI boom is underpinned by a complex physical supply chain, with critical components that are often overlooked. From real estate and telecom to data center construction and electrical hardware, these hidden elements are emerging as the true bottlenecks.
GEP empowers hyperscalers and providers across this ecosystem with smart solutions to manage a delicate balance: performance and deployment speed on one side, cost efficiency and agility on the other. This resource center brings together expert insights and actionable strategies to help scale data center fleets optimally — like a well-diversified financial portfolio.
What’s Really Powering the AI Revolution?
AI models, chips and data dominate headlines, but the infrastructure beneath them is the true battleground. This visual illustrates the full scope of AI’s physical supply chain, from visible investments to hidden dependencies.
Our Latest Thinking on the Supply Chain of AI
The AI Race Isn’t Just About Tech Superiority — It's the Supply Chain, Stupid!
Why AI Hyperscalers Need to Recode Their Supply Chain Strategy
AI’s Achilles’ Heel: The Supply Chain Crisis Holding Back the Future of AI
Data Center Maintenance Costs: The Hidden Risk to AI Profitability (And How to Fix It)
GEP’s Supply Chain of AI Solutions
AI infrastructure is evolving rapidly — and with it, the supply chains that support it. Hyperscalers and digital leaders must now prioritize agility, resilience, and cost efficiency across every phase of the AI supply chain, from data center siting and construction to ongoing operations.
GEP brings together strategic consulting, market intelligence, and AI-powered software to help enterprises scale smarter and stay ahead.
Our Approach
The race to scale AI infrastructure has entered a new phase.
In 2025, the priority has shifted from raw compute power and speed of deployment to smarter, more cost-efficient growth — and the ability to adapt as workloads shift from training to inference.
GEP helps leading AI hyperscalers move faster and spend smarter. With deep expertise in the AI ecosystem and a proven track record in improving agility and efficiency, we empower our clients across every phase of the supply chain — from site selection and construction to long-term operations and optimization.
Whether it’s developing your energy strategy, sourcing critical infrastructure, or managing third-party providers, we help you build and maintain AI infrastructure that’s scalable, sustainable, and resilient.
Our Supply Chain of AI Solutions
STRATEGY & PLANNING
- Global Site Selection Market Intelligence
- Data Center Service Provider Market Intelligence
- Materials Demand Forecasting
- Energy Strategy
- Budgeting and Should-Cost Modeling
- Cost Takeout Strategy
CONSTRUCTION
- Data Center Construction Management
- Energy Infrastructure Construction Management
- Data Center Sourcing and Procurement
- Integrated Supply Management — Buy-Hold-Sell
- Integrated Risk Management
MAINTENANCE
- Service Provider Management
- Cost Takeout and Continuous Improvement
- Sourcing and Procurement
Why GEP
GEP is a trusted partner to the world’s largest and most advanced technology companies, helping them build resilient, cost-effective supply chains that support the rapid evolution of AI.
End-to-End Supply Chain Expertise
We support every stage of AI hyperscaler expansion — from global site selection and energy strategy to datacenter construction, third-party management, and ongoing cost optimization.
AI Ecosystem Insight
With deep knowledge of the evolving AI landscape, we tailor strategies that align with shifting infrastructure demands — from training to inference, and beyond.
Proven Cost Optimization
GEP is an industry leader in cost takeout programs, helping hyperscalers uncover savings opportunities and enhance margins across direct and indirect spend.
Integrated Supply & Risk Management
Our integrated supply solutions and risk frameworks ensure supply continuity and resilience in a high-velocity environment.
Global Reach with Local Execution
Operating in 25+ countries, we combine local market expertise with global scale to deliver fast, informed decisions — wherever you grow.
Ready to Rethink Your AI Datacenter Scaling Strategy?
As enterprise demand for AI grows, so does the pressure on data center scaling teams. GEP helps you evaluate trade-offs, reduce risk, and support AI goals with a flexible, forward-looking scaling strategy. Let’s talk.
Frequently Asked Questions
AI models require massive compute power, specialized chips, high-bandwidth data transfer, and energy-intensive infrastructure — all of which rely on a complex, multi-dimensional supply chain.
Hyperscalers are expanding their compute capacity at an unprecedented pace. But the physical supply chain behind data centers depends on industries that aren’t accustomed to moving this fast. The stakes are high: a years-long lead time on an electrical transformer could cost a hyperscaler its global lead in the AI race.
To make things even more challenging, AI breakthroughs are happening every month — triggering tectonic shifts in infrastructure requirements. This means the supply chain must operate not only at unprecedented speed, but also with extraordinary agility. As a result, the pressure on the teams building this supply chain — and their providers — is immense.
In recent years, companies have poured resources into vertically integrated, custom-built AI infrastructure in an all-out race for performance. But as inference workloads grow exponentially, this high-cost approach is becoming unsustainable.
With costs surging and demand increasingly difficult to predict, leading hyperscalers are shifting to modular, flexible supply chain strategies that balance performance, cost-efficiency, and speed.
GEP helps enterprises navigate the growing complexity of AI-driven demand. As a partner of choice across the most infrastructure-intensive segments of the supply chain, GEP offers deep expertise and end-to-end support. Examples of our services include:
Providing global market intelligence to help select optimal sites for AI data centers
Project-managing data center construction to balance speed and cost
Orchestrating the full buy-hold-sell supply chain across dozens of data centers as they come online
Reducing maintenance costs at existing data centers to meet the economics of inference
Identifying and negotiating with external providers to build agility into the supply chain — cost-efficiently
Beyond chips and models, AI depends on six often-overlooked but critical components:
- Data center construction
- Power generation
- Telecom infrastructure
- Real estate
- Data center infrastructure equipment
- Compute hardware
Without these, AI deployments stall — no matter how advanced the models are.
Yes — strategic externalization is gaining traction. Hyperscalers are increasingly leasing compute capacity, partnering on power sourcing, and tapping third-party data centers to reduce capital outlays and increase scalability. But this comes with trade-offs in customization and control.