Grid-Enhancing Tech (GETs) Could Double Transmission Capacity as SPARK Funding Deadline Looms

The fundamental driver of grid modernization is no longer just climate policy or electric vehicles. It is the exponential adoption of artificial intelligence, which is reshaping the entire energy landscape. For decades, U.S. electricity demand was essentially flat. That changed in 2025, when retail demand for electricity climbed 2% year-on-year, marking the first significant rise in decades. This shift is overwhelmingly powered by data centers, which have become a dominant force behind the surge.

The scale of this new demand is staggering. Data center electricity consumption has quintupled in the past 10 years and grown 150% in the last five years. This isn't linear growth; it's an S-curve acceleration. The latest data point is a record-setting signal: in January 2026 alone, $25.2 billion in data center construction starts was announced, including two $10 billion megaprojects. This is the new grid paradigm. Utilities are no longer just managing a steady flow of power to homes and factories; they are being asked to deliver the immense, concentrated compute power required for AI training and inference.

Meeting this exponential adoption curve without building entirely new transmission infrastructure is the core challenge. The U.S. grid, with over 600,000 miles of aging lines, was not designed for this kind of dynamic, high-density demand. The solution lies in optimizing the existing rails. This is where grid-enhancing technologies (GETs) emerge as the critical infrastructure layer. They allow utilities to double transmission capacity, reduce congestion, and improve reliability by leveraging what's already there. In the race to power the AI paradigm, GETs are the essential upgrade that enables the grid to keep pace.

GETs as Exponential Adoption Enablers: Doubling Capacity on the Existing S-Curve

The core mechanism of grid-enhancing technologies is elegant in its simplicity. They use a blend of hardware and software to optimize existing transmission infrastructure, effectively doubling capacity and reducing congestion without the delays and costs of building new lines. This is the first principle of infrastructure scaling: leverage what's already there. Technologies like Dynamic Line Ratings adjust power limits in real time based on weather, while Advanced Power Flow Controllers actively manage flows to alleviate bottlenecks. The result is a grid that can handle more power, more efficiently, on the same physical rails.

This optimization is not a niche fix; it's becoming a critical market layer. The North America smart grid market, which includes GETs, is projected to grow at a 10.6% compound annual rate, expanding from $18 billion in 2025 to $44.5 billion by 2034. This trajectory signals a maturing infrastructure layer, moving from pilot projects to a standard tool in the utility's arsenal. The market growth is a direct response to the exponential adoption curve of AI and data centers, which are pushing demand into uncharted territory.

Policy acceleration is now unlocking this potential. In 2025, nine states passed new GETs legislation, creating frameworks that require utilities to evaluate these technologies for cost-effectiveness before pursuing new transmission. This legislative wave, from Utah to Delaware, is a powerful signal that the regulatory environment is adapting to the new paradigm. It removes a key friction point, allowing utilities to deploy solutions that double capacity on the existing S-curve rather than embarking on a decade-long, multi-billion dollar build-out.

The bottom line is resilience. By enhancing the grid's ability to manage dynamic, high-density loads, GETs improve reliability against extreme weather and other shocks. In the race to power the next technological paradigm, these technologies are the essential upgrade that allows the existing rails to carry the exponential load.

Policy Funding as the Financial Rail for Exponential Growth

The exponential adoption curve of AI-driven data centers is hitting a critical bottleneck: the financial rails for upgrading the grid are now being laid down. This is where public funding becomes the essential catalyst, providing the capital to accelerate transmission upgrades and deploy grid-enhancing technologies at scale. The U.S. Department of Energy's recent $1.9 billion SPARK funding opportunity is a prime example. This competitive pot, part of the broader GRIP program, is explicitly designed to fast-track projects that double existing transmission capacity. It prioritizes reconductoring and advanced technologies that can be implemented quickly, directly targeting the need to manage new loads without decade-long build-outs.

This funding isn't just a one-off grant; it's a signal that the federal government is treating grid modernization as a national infrastructure priority. The Bipartisan Policy Center has identified continued federal funding for GRIP as a key policy solution to support GETs adoption. This consensus view underscores that sustained capital infusion is necessary to move these technologies from pilot projects to a standard layer of the grid. The funding acts as the financial rail that enables the exponential growth of the GET infrastructure layer, turning proven concepts into widespread deployment.

The urgency is driven by a massive, speculative backlog. The data center industry is projected to bring online over 100 gigawatts of new demand, a load equivalent to ten New York Cities. Utilities are already swamped with interconnection requests, creating a system-wide strain. In this context, tools like GETs are not optional-they are the operational necessity for managing load efficiently on the existing network. Without the financial rails provided by programs like SPARK, the grid would be forced into a costly, slow-motion expansion that cannot keep pace with AI adoption.

The bottom line is that policy funding is the missing link in the S-curve. It provides the capital to deploy the technologies that optimize the rails, ensuring the grid can handle the exponential demand surge. This is infrastructure investing at the paradigm shift level.

Catalysts, Exponential Adoption Risks, and What to Watch

The final frontier for the grid-enhancing technology S-curve is where policy meets execution. The near-term catalyst is a hard deadline: utilities and developers must submit concept papers for the $1.9 billion SPARK funding by April 2, 2026. This isn't just a grant application; it's a trigger for a cascade of project announcements and planning. The funding's explicit focus on reconductoring and advanced technologies that double existing capacity means the projects selected will directly address the exponential demand curve. Success here could accelerate the deployment of GETs from a niche optimization tool to a standard layer of the grid.

Yet the path forward is fraught with risks that could derail the adoption curve. The most immediate threat is policy misalignment, exemplified by the "energy subtraction" agenda in the PJM region. By forcing nearly 17 gigawatts of reliable baseload power offline, this policy has created a system-wide strain. It increases grid vulnerability and electricity prices, directly counteracting the reliability gains that GETs are meant to provide. In a region where data center demand is projected to grow by up to 30 gigawatts, this policy creates a dangerous friction between new load and retiring supply. It's a classic case of regulatory overreach that could amplify congestion and make the case for transmission upgrades more urgent, but also more politically fraught.

The primary metric to monitor is the adoption rate of GETs within utility interconnection queues and transmission planning. This is the true signal of penetration into the exponential demand curve. Are utilities and regional planners like PJM actively using these technologies to manage the backlog of data center requests? The evidence shows they are beginning to act, with PJM approving projects to solve reliability needs driven by accelerated load growth. But the real test is in the numbers: how many of the hundreds of pending interconnection requests are being paired with GET solutions versus traditional, slow-build transmission? A high adoption rate here would signal that the infrastructure layer is being built at the same pace as the demand it must serve. A low rate would highlight a critical bottleneck, where policy and planning lag behind the S-curve of AI-driven power needs.

The bottom line is that the SPARK deadline is the near-term spark. The energy subtraction risk is the immediate friction. And the adoption rate in planning queues is the ultimate gauge of whether the grid can keep pace with the next paradigm.