Optimizing Infrastructure Investments: Utilizing Emerging AI Tools to Surgically Strengthen the Grid Amidst Growing Demand and Complexity

Electric utilities across the U.S. are bracing for an unprecedented surge in new electricity demands from data centers supporting AI advancements and expanding consumer and commercial fleets of electric vehicles (EVs). In December 2024, Canary Media reported a projected new load growth of nearly 128 GW over the next 5 years. These new loads pressure grid operators to rapidly modernize their aging (and largely antiquated) networks and infrastructure. IOUs, municipal utilities, and co-ops face a daunting challenge: ensuring continued grid reliability while accommodating fast-growing, power-intensive sectors and evolving consumer needs. Despite record-breaking capital expenditures, the scope of needed upgrades still vastly surpasses what current investment levels and resources can achieve.

This Old Grid: Record Capital Investments Are Still Not Enough

According to a recent Reuters article, U.S. utilities are ramping up capital expenditures to meet the growing demand from power-hungry sectors, with nine profiled utilities raising their forecasted capital expenditures by an average of 22% between 2025 and 2027. Yet, despite billions upon billions of dollars being allocated, this funding is only “scratching the surface" of what is needed to fully upgrade the nation’s aging grid infrastructure and meet the needs of emerging industries, says J.P. Morgan.

The sheer age of many critical components adds urgency to these investments. Per the U.S. Department of Energy (DOE), nearly 70% of the nation’s grid is over 25 years old. Similarly, the millions of power transformers along several million miles of distribution grid lines have an average age of 35 years—meaning a very significant percentage of them are still in operation beyond their expected lifespan of 30-40 years!

The age and condition of existing equipment place our grid in a precarious position, particularly as extreme weather events increase in frequency and severity in many regions. These unpredictable and often unprecedented system shocks place even more strain on already overburdened equipment.

Inspections: Too Infrequent and Inefficient for Aging Infrastructure

According to the EIA, utilities spend approximately $15B on electrical distribution operations and management (O&M) annually, with fully half of that budget dedicated to overhead lines. Despite these significant O&M budgets, grid operators are often constrained in how frequently they can inspect poles and pole-mounted assets, with inspection cycles ranging from once per year to once every 15 years depending on the location, type of inspection, and local regulations. The variability in inspection cycles can create blind spots in identifying critical maintenance needs, especially as the grid's assets near their end-of-life and extreme weather events become more frequent. Prolonging these inspections can lead to equipment failures at the worst possible times—such as transformers overheating and failing when hyper-localized load patterns change due to new usage patterns and demand from EVs, an increasingly remote workforce, extreme weather, and other new loads. In addition to maintenance issues, the lack of asset-level visibility can create challenges as grid operators seek to make the most efficient uses of capital for their grid upgrades.

The Role of AI and Emerging Technologies in Targeted Upgrades

The grid’s future depends on a more strategic and surgical approach to upgrades. This is because the grid will not face these emerging stresses uniformly; specific substations and even individual transformers in high-demand areas will bear the brunt of new load requirements. This makes it imperative for quality data sources to inform the decision-making process of where and how upgrades are prioritized to ensure the most urgent and critical needs are addressed.

A range of innovative AI-based sensor and grid monitoring technologies, such as equipment-mounted line and transformer monitoring sensors, drones, and vehicle-mounted grid asset inspection platforms like Noteworthy AI’s Inspect platform, offer solutions to enhance asset visibility and expand ongoing inspection coverage without a proportional cost increase. These new resources are invaluable to utilities, as they continuously update key data points to monitor asset health and provide real-time insights to proactively address maintenance needs before they escalate into critical failures. Scaled applications of these emerging data-driven technologies can enable utilities to maximize the coverage of their limited resources, ensuring that capital and operational funds are allocated effectively and optimizing grid reliability and resilience against an array of challenges.

Preparing for the Future

As the U.S. electric grid undergoes this transformation, utilities must balance maintaining current service levels with preparing for a future of increased complexity and demand. Enhanced visibility into asset conditions and strategic and targeted infrastructure investments (supported by AI and analytics tools), will be essential to ensuring grid resilience.

To rise to these challenges, utilities should consider how effectively they are incorporating actionable steps like the ones below into their organization playbook:

Dedicate Budget to Emerging Technologies: Allocate a portion of annual budgets specifically to evaluating and experimenting with emerging technologies that align with grid modernization goals. This proactive funding ensures utilities stay ahead in testing and adopting innovative tools.
Define Clear Pilot Objectives: Establish well-defined objectives with vendors for technology pilots, focusing on addressing the specific challenges within your service territory and grid conditions. This targeted approach helps ensure pilots deliver actionable insights and measurable results.
Incorporate Scaling into Annual Plans: Build funding mechanisms into annual planning cycles to seamlessly transition successful pilots into broader deployments. This planning avoids delays in scaling impactful solutions, maximizing the benefits of tested innovations.
Streamline Onboarding Processes: Review and optimize procurement, onboarding, and contracting processes to enable faster adoption of proven technologies. Eliminating unnecessary administrative hurdles helps ensure the numerous teams and stakeholders at utilities can implement solutions that demonstrate value more efficiently.
Focus on Long-Term ROI: Balance immediate operational needs with strategic investments in tools that offer long-term cost savings and resilience improvements. Adopt metrics that account for lifecycle benefits, not just upfront costs, when evaluating new solutions.
Leverage AI and Analytics for Targeted Investments: Use AI-driven analytics and monitoring tools to identify and prioritize infrastructure investments based on real-time asset health and localized demand trends. This ensures capital is deployed where it will have the greatest impact.

With careful planning, advanced technology, and a focus on the most critical upgrades, utilities will be poised to overcome the challenges ahead and build a grid that is resilient, reliable, and ready to face a future of ongoing innovation and change.