Grid StrAIn Part 5 — The Hidden Infrastructure Crisis: Why AI’s Energy Demand Exposes an Aging Grid
AI’s energy growth is accelerating faster than many expected, and the grid’s aging backbone is being pushed to the brink. From transformer shortages to transmission bottlenecks and permitting delays, structural weaknesses in critical infrastructure are being exposed by this rapid shift in demand.
Without proactive action, AI’s exponential load growth could push fragile systems beyond their limits. Utilities need new strategies to stay ahead.
A New Load on an Old Grid
AI-driven energy demand is always-on and growing faster than originally projected. Data centers, once built for more predictable IT loads, are now consuming unprecedented amounts of electricity to power generative AI models, training, and inference cycles.
According to the International Energy Agency, global data center demand is projected to double or triple by 2030. In North America alone, AI-related usage is creating high base loads with fewer off-peak cycles, putting additional stress on transformers, transmission corridors, and substation equipment originally designed for more traditional load curves.
These trends are already forcing utilities to reevaluate reliability strategies, and they expose deeper systemic risks.
The Transformer Bottleneck
Perhaps the most urgent challenge lies with transformers. The U.S. is facing a well-documented shortage of large power transformers, with lead times for delivery now reaching three to five years in many cases.
Multiple factors are driving this bottleneck: limited domestic manufacturing capacity, surging global demand, and ongoing trade policy volatility. Section 232 tariffs on electrical steel and shifting global tariffs on transformer components continue to add cost uncertainty and slow procurement, compounding the supply constraints just as AI-driven loads are accelerating demand for grid upgrades.
At the same time, the existing fleet is aging rapidly. Many transmission-class transformers are operating well beyond their original design life, with deferred maintenance and replacement backlogs adding to the risk. As AI-driven base loads continue to grow, they will only accelerate the aging process and increase thermal stress across these critical assets.
Utilities must now adopt smarter, data-driven approaches to transformer fleet management. Condition-based strategies can help mitigate risk, using diagnostics like:
These tools help utilities prioritize limited replacement resources, safely extend the life of existing assets, and prevent unexpected failures as transformer supply constraints continue.
Transmission Challenges and Permitting Delays
AI’s energy demand isn’t isolated to transformers. It also places new strain on already congested transmission corridors, which are notoriously difficult to expand or modernize.
Current estimates suggest that major new transmission lines face permitting delays of 7 to 10 years in many regions. Yet without those upgrades, more energy must flow through aging infrastructure, often exceeding original design tolerances.
As transmission assets face greater wear and thermal loading, substation components, including circuit breakers, bushings, arresters, and protection systems must handle elevated stress and protect the grid from cascading faults.
Utilities can mitigate these risks with modern protection testing and monitoring solutions, ensuring that even in strained transmission corridors, the system remains stable and secure.
The Path Forward: Invest, Monitor, Modernize
AI’s rapid growth is exposing hidden weaknesses—but it also provides an opportunity to modernize smarter.
Utilities can get ahead by:
- Using advanced diagnostics to prioritize where limited resources should go.
- Implementing condition-based maintenance to safely extend asset life.
- Leveraging fleet-wide data and trends to optimize replacement planning and manage risk during transformer shortages.
- Enhancing protection and substation reliability to safeguard transmission corridors operating under stress.
Doble’s condition monitoring tools and protection testing services are already helping utilities across North America shift from reactive to proactive—and prepare their grids for the realities of tomorrow’s load patterns.
Strengthening Infrastructure for What’s Ahead
AI’s energy growth is inevitable. The grid’s current limitations are not.
Transformer shortages, transmission delays, and an aging asset base won’t resolve overnight, but with the right strategies, utilities can manage these risks, optimize resources, and build resilience for the future.
At Doble, we’re committed to helping utilities strengthen their infrastructure, protect critical assets, and maintain reliability—because the future of AI-powered energy depends on the decisions we make today.
Additional Information:
- Grid StrAIn: AI & Grid Reliability Part 1—The AI Energy Crunch: How Data Centers Are Reshaping Grid Reliability
- Grid StrAIn Part 2 — How Utilities Can Get Ahead of AI’s Energy Strain — Before It’s Too Late
- Grid StrAIn Part 3 — AI vs. AI: Can Artificial Intelligence Solve the Grid Strain It’s Creating?
- Grid StrAIn Part 4 — Utilities Are Betting on AI to Spot Failures Before They Happen
