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Read articleAI is turning digital infrastructure into a race for power, capital and physical delivery capacity rather than a simple expansion of computing demand
We see data-center and infrastructure businesses balancing extraordinary demand expectations with grid constraints, financing risk, technology change and asset concentration.
Data-center markets enter September 2026 amid one of the largest infrastructure build-outs associated with the AI cycle. Yet compute demand alone does not guarantee attractive assets. Power availability, grid connection, cooling, construction capacity and financing increasingly determine where capacity can actually be delivered, while rapid changes in hardware and computing efficiency create longer-term utilization and obsolescence questions. Capital requirements are becoming large enough to reshape financing structures and concentration risk. The strategic challenge is therefore matching infrastructure commitments with credible demand, energy access and technological flexibility rather than treating announced AI capacity as equivalent to durable economic value.
Focus
Power availability is becoming the real constraint on the AI infrastructure boom
Data-center demand is accelerating while grid congestion, connection queues and construction economics limit where capacity can actually be built.
Read nowStrategic Challenges
Can data-center growth outrun the power systems required to support it?
The challenge is securing energy, land and connectivity while AI workloads raise density and shorten infrastructure planning horizons.
Read nowStrategic Impacts
Data-center strategy is becoming inseparable from energy strategy
Grid access, on-site generation and storage increasingly determine location economics as AI-driven computing demand expands.
Read nowObserved Patterns
Data-center developers often secure land before securing a credible power pathway
Sites can remain commercially stranded when grid capacity, interconnection timelines and local infrastructure fail to support planned density.
Read nowStrategic Challenges
Can data-center growth outrun the power systems required to support it?
The challenge is securing energy, land and connectivity while AI workloads raise density and shorten infrastructure planning horizons.
Read nowStrategic Impacts
Data-center strategy is becoming inseparable from energy strategy
Grid access, on-site generation and storage increasingly determine location economics as AI-driven computing demand expands.
Read nowObserved Patterns
Data-center developers often secure land before securing a credible power pathway
Sites can remain commercially stranded when grid capacity, interconnection timelines and local infrastructure fail to support planned density.
Read nowIndustry Challenge
Data-center growth is colliding with power, grid and capital constraints
Demand for digital infrastructure is accelerating faster than many power systems, permitting regimes and equipment supply chains can absorb. AI workloads are raising density, cooling and reliability requirements while grid connection queues extend project timelines. At the same time, investment needs are becoming too large for traditional balance-sheet funding alone. The challenge for operators is to secure power, sites, equipment and financing in the right sequence, while avoiding stranded capacity and maintaining resilience as technology architectures and customer requirements evolve.
Future Outlook
Digital infrastructure will become an integrated power-and-compute ecosystem
The next generation of data centers will be designed around the interaction between compute, energy, cooling and capital rather than treated as standalone real-estate assets. Greater use of on-site generation, storage, advanced cooling, flexible demand and AI-enabled operations will be required as power density rises. Location strategy will increasingly reflect grid availability, energy economics, fiber connectivity and geopolitical constraints. Operators that can coordinate utilities, capital providers, technology vendors and customers will gain an advantage in scaling scarce capacity.
Market Outlook
AI is driving a historic infrastructure buildout, but power is the bottleneck
Data-center investment remains one of the strongest infrastructure themes in 2026, driven by hyperscale cloud and AI demand. The IEA expects global data-center electricity use to roughly double from 2025 to 2030, with AI-focused facilities growing much faster than the overall market. Near-term growth is constrained by grid connection delays, transformers, generation capacity, cooling and financing. Power demand is therefore becoming a central determinant of site value and project timing, while capital markets are taking a larger role in funding expansion beyond the balance sheets of operators.
POV
The next data-center shortage may be measured in megawatts, not buildings
Compute demand can grow faster than electricity infrastructure, making power access the defining competitive asset of the sector.
Read nowOur approach
Evaluate digital infrastructure by connecting compute demand with the physical and financial constraints required to serve it
Our approach� links customer demand and compute architecture with power, grid access, land, cooling, fiber, construction capacity and capital. We test how these variables interact at site and portfolio level and distinguish contracted or structurally defensible demand from speculative capacity requirements. Technology scenarios are incorporated because changes in chips, density or computing architecture can alter the economics of long-lived assets. This integrated view helps determine where infrastructure can create durable value, what bottlenecks determine timing and how financing and development risk should influence portfolio choices.
The data and estimates presented are indicative and intended for illustrative purposes. Actual outcomes may vary based on each company’s specific context, market conditions, operating model, implementation choices, and the quality and consistency of execution, including actions undertaken by the client.
Keypillars
Explore the key pillars that define this capability and shape how we create focused, measurable business impact.
Infrastructure economics
Understands capital intensity, utilization, energy cost, capacity, and return profiles across data-center and digital-infrastructure assets
Operating architecture
Examines power, cooling, connectivity, land, hardware, redundancy, and service requirements across mission-critical facilities
Capacity dynamics
Tracks AI demand, cloud growth, grid constraints, chip density, sovereign requirements, and regional capacity expansion across the sector
Can your digital infrastructure strategy keep pace with accelerating demand for compute, power and connectivity?
Get in touch with our Data centers and digital infrastructure team to address capacity, investment, energy and infrastructure decisions.
Get in touchStrategic Framework
Explore our Strategic Framework
Autonomous AI agents are changing how work is executed, enabling adaptive processes that respond intelligently to changing conditions instead of following predefined rules.
Discover our framework01. Map infrastructure
Assess data centers, cloud regions, fiber, power, land, connectivity, customers, and capacity pipelines
06. Track constraints
Monitor power queues, permits, construction, occupancy, pricing, connectivity, and hyperscaler demand
05. Define expansion
Prioritize locations, capacity, customer segments, infrastructure partnerships, and investment timing
02. Trace demand
Examine AI workloads, cloud growth, latency, sovereignty, power availability, regulation, and enterprise demand
03. Assess position
Evaluate footprint, power access, utilization, customer mix, connectivity, cost structure, and expansion potential
04. Model capacity
Test demand, power, pricing, build-out, regulation, technology, and capital scenarios by market
How we help
Support digital-infrastructure businesses in translating exceptional demand expectations into disciplined development, portfolio and capital decisions
We help operators, developers and investors evaluate markets and sites, customer demand, power strategy, capital requirements and portfolio exposure across data centers and related infrastructure. We can support growth strategy, market entry, development sequencing, investment prioritization, partnerships, operating models and risk scenarios. The objective is to distinguish capacity with durable strategic and economic foundations from projects whose returns depend too heavily on optimistic assumptions about demand, financing, technology or infrastructure availability.
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Data center growth strategy
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Data center market selection
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Data center capacity planning
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AI infrastructure strategy
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Hyperscale customer strategy
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Colocation strategy
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Edge data center strategy
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Power sourcing strategy
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Power availability risk
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Data center energy optimization
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Liquid cooling strategy
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Data center site selection
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Interconnection strategy
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Data center pricing strategy
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Data center investment strategy
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Construction delivery optimization
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Digital infrastructure resilience
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Data center sustainability strategy
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Data center portfolio optimization
Explore our FAQs
Find answers to the most common questions about this service, including key features, processes, and practical considerations. Explore our FAQs for additional insights and guidance.
Power availability, land, connectivity, utilization, capital cost and customer demand determine the attractiveness of capacity investments.
AI increases demand for high-density compute, power and cooling while changing infrastructure requirements and capacity planning.
Power constraints can determine where capacity can be built, how quickly it can scale and whether projected economics remain viable.
Assess power, connectivity, regulation, demand, land and development timelines rather than focusing on construction cost alone.
Grid limitations, permitting, equipment lead times and uncertain demand can create significant timing and capital exposure.
Energy efficiency, power sourcing and water use increasingly influence operating economics, permitting and location attractiveness.
When committed demand and realistic utilization do not support the capital required under plausible pricing and power-cost scenarios.
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