Overview of Gartner’s December 2025 finding
Gartner’s December 2025 research highlights an emerging constraint for supply chain managers: electricity. The firm says the rapid adoption of artificial intelligence is driving energy demand in ways that threaten continuity, cost stability, and operational resilience across supply networks.
Projected data center energy growth through 2030
Gartner projects that global electricity consumption by data centers will more than double by 2030. The analysis identifies AI workloads as the primary engine behind that surge, reshaping projections for power needs over the remainder of the decade.
Rising energy prices and equipment costs
The report points out that electricity prices are climbing at almost twice the pace of general inflation. At the same time, the prices of critical grid and data center components — including transformers, cables, and essential metals — are increasing, adding to the overall cost pressure facing companies.
Key contributors to electricity load growth
Gartner attributes the bulk of global electricity load growth to a few major trends. The research estimates that roughly 90% of the additional electricity demand by the end of the decade will come from:
- AI adoption and its expanding compute requirements
- Industrial electrification as more industries convert from fossil fuels to electric power
- Population growth driving broader increases in baseline demand
Strategic risk to grids and supply chains
The report warns that the pace and concentration of AI-driven demand are testing century-old energy infrastructure. In striking language, Gartner says, "AI demand is expanding like a high-pressure hose being forced into a century-old energy grid," and cautions that grid reliability could transition from a taken-for-granted utility to an active strategic constraint for businesses.
Implications for supply chain leaders
Supply chain leaders should treat energy availability and grid resilience as core risk factors. Rising electricity and equipment costs, coupled with concentrated demand growth, can affect sourcing, production continuity, and total cost of ownership for goods and services that rely on data-center intensive AI.
Actionable considerations and next steps
Organizations may need to reassess supplier risk models, factor electricity and infrastructure constraints into scenario planning, and collaborate with energy providers on capacity and resilience solutions. Investing in energy-efficient AI architectures and exploring diversified power sources can also reduce exposure.
Further reading
For the complete analysis and additional detail, see the full Gartner research
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