Research & Sources
Sources
Clarke's positioning responds to a clearly documented gap: AI infrastructure is scaling at unprecedented speed, but inconsistent capacity models, speculative interconnection requests, and the absence of standardized definitions are creating billion-dollar planning uncertainties across the industry.
AI Infrastructure Growth Acceleration
International Energy Agency (2025)
Energy and AI
Read Report"Global data center electricity demand is projected to exceed 1,700 TWh by 2035 in the Lift-Off Case—reaching 4.4% of global electricity demand—with AI workloads driving the majority of this growth."
RAND Corporation (2025)
AI's Power Requirements Under Exponential Growth
Read Report"Global AI data center power demand could reach 68 GW by 2027 and 327 GW by 2030, compared with total global data center capacity of just 88 GW in 2022. Individual AI training runs could require up to 1 GW in a single location by 2028."
Goldman Sachs (February 2025)
AI to Drive 165% Increase in Data Center Power Demand by 2030
Read Report"Global power demand from data centers will increase 50% by 2027 and by as much as 165% by the end of the decade, with much of this growth concentrated in North America."
Deloitte (2024)
The AI Era: Meeting Power Demands for Data Centers
Read Report"The AI-driven data center expansion represents the largest compute infrastructure buildout in history, with power requirements outpacing current grid capacity in key markets."
Inconsistent Capacity Modeling & Metrics
IEA 4E EDNA (2025)
Data Centre Energy Use: Critical Review of Models and Results
Read Report"Estimates and projections for 2020 range from less than 200 TWh to 1,200 TWh, while projections for 2030 range from just over 200 TWh to nearly 8,000 TWh—a factor of almost 40—causing confusion for policymakers and decision-makers."
Fragmented Demand Signals & Planning Uncertainty
World Resources Institute (September 2025)
Powering the US Data Center Boom: Why Forecasting Can Be So Tricky
Read Article"Modeled energy use projections through 2030 range from 200 TWh/year to over 1,050 TWh/year. Utilities are being flooded with 'speculative' interconnection requests—duplicate filings and 'phantom' load that will never be built—distorting load forecasts and utility resource planning."
CNBC (October 2025)
Utilities Grapple with Multibillion Question: How Much AI Data Center Power Demand Is Real?
Read Article"Tech companies are shopping the same big projects around to multiple utilities as they look for quickest access to power, making it difficult for utilities to determine how much power generation they will actually need."
Utility Dive (November 2025)
A Fraction of Proposed Data Centers Will Get Built. Utilities Are Wising Up.
Read Article"Conservatively, five to ten times more interconnection requests exist than data centers actually being built. Excess requests sap utilities' study resources, delay legitimate projects, and distort long-range planning—risking costly system overbuilding."
The Need for Standardization & Transparency
GridLab (March 2025)
Practical Guidance and Considerations for Large Load Interconnections
Read Report"The electricity sector is experiencing a surge in speculative requests stemming from fragmented, opaque processes. Introducing a standardized and transparent load-side interconnection process is essential to control speculation and provide clarity for utilities and developers."
Brookings Institution (2024)
The Future of Data Centers
Read Article"The rapid expansion of AI infrastructure requires new frameworks for coordination between technology companies, utilities, and policymakers—built on shared definitions and transparent methodologies."
These sources establish Clarke's market context: unprecedented AI infrastructure scaling, capacity models diverging by factors of 40x, speculative demand distorting utility planning, and explicit calls for standardized definitions and transparent methodologies—the foundational challenges Clarke addresses.