Why the software your maintenance team uses every day is the most overlooked piece of America's energy puzzle.
Industry experts are increasingly sounding the alarm about the growing strain on the power grid driven by artificial intelligence (AI) development and rapidly rising demand for energy and computing capacity. Some argue that advanced nuclear energy may be one of the few scalable options of meeting future electricity needs. Recent industry data makes it clear: demand is accelerating quickly, and existing infrastructure may struggle to keep pace.
But the question that seems to be rarely addressed in manufacturing operations and facilities management is not how to generate more electricity, but how to maximize the effective use of the electricity already being produced.
When macro energy problems arise, the corporate world naturally looks for macro solutions. We talk about building reactors, upgrading transmission lines and funding massive infrastructure projects. These conversations are important. But they skip a critical chapter of the story, one that doesn’t involve years of regulatory approvals and massive budgets. Instead, it involves the people who show up every single day to manage the equipment we already have.
Every single kilowatt that is wasted by neglected or undermaintained equipment strains a power grid we all share and raises energy costs we all pay. This is no longer just a data center problem or a manufacturing problem. It is an operational discipline problem. Yet some of the systems best positioned to address it are rarely part of broader energy discussions: the platforms organizations already use to manage maintenance, assets, and operational performance.
The Numbers Are No Longer Abstract
The reality of our energy situation is laid out plainly by recent grid reliability data in NEMA’s “A Reliable Grid for an Electric Future” Reliability Study. Electricity demand in the United States is projected to grow by more than half over the next twenty-five years. Data centers alone represent a 300% projected growth in energy consumption over the next decade. Artificial intelligence demand is expected to account for a quarter of all data center load by the end of the decade, with certain workloads requiring 10 times the power of conventional computing.
One specific data point should alarm every operations, facilities, infrastructure, and manufacturing leader. More than 90% of all projected data center consumption growth between now and mid-century will happen in the next 10 years.
Our national power grid was simply not built for this rate of change. Data centers have already jumped from using roughly 2% of United States’ electricity in 2018 to around 5% today. They are expected to easily clear 10% in a few short years. Regional grids like the Pennsylvania-New Jersey-Maryland interconnection (PJM) and the Electric Reliability Council of Texas (ERCOT), which sit at the heart of industrial and digital infrastructure growth, are seeing the fastest consumption increases in the nation. This steep growth curve does not allow for a slow or graceful transition.
The Operational Blindspot
While industrial leaders naturally look for macro solutions, whether upgrading transmission lines, deploying dynamic line ratings, or building digital substations, these necessary investments are not sufficient on their own.
The missing link lies in facility-level performance optimization. Industry groups point out that fully deploying energy-saving technologies, optimizing cooling systems, managing airflow and using efficient transformers can dramatically reshape a facility’s energy footprint. Scheduling high strain operations for off-peak times decreases peak demand, reduces corporate costs, and boosts overall grid reliability.
This means that individual, facility-level operational decisions have become a direct lever on grid stability itself. This is no longer just a conversation about lowering next month’s utility bill. This is a conversation about national infrastructure survival.
Yet, the framework that governs these daily operational decisions, whether the facility relies on a localized Computerized Maintenance Management System (CMMS) or a broader Enterprise Asset Management platforms (EAM), is often viewed by executives as a mere administrative tool for tracking repairs. The industry has not connected the dots between everyday maintenance systems and broader goals around energy efficiency, reliability, and preservation.
What True Efficiency Looks Like
When corporate leadership thinks about energy management, they tend to look at high-level utility meters. But a well-managed maintenance framework is an energy management system whether it is labeled as one or not. Every preventive maintenance task tracked and every industrial asset monitored across a facility can fundamentally serve as an energy data point.
Consider the reality of a standard industrial or data center floor. Chillers running with fouled heat exchangers, cooling towers with degraded fill or variable frequency drives that have drifted from their optimal setpoints are not just minor maintenance failures. They represent continuous, invisible energy waste. When equipment struggles against its own neglected components, it draws significantly more current to deliver the exact same output.
Timing is another massive variable. Running heavy backup systems or testing generation equipment during peak demand periods creates intense grid stress at the worst possible moment. True operational discipline allows a facility to shift cooling loads to off peak hours, reduce peak power draw and participate in demand response programs that reward companies for helping stabilize the local grid.
The documentation and execution of that precise strategy cannot happen on spreadsheets or sticky notes. Achieving that level of operational consistency requires disciplined processes and reliable systems that help teams coordinate maintenance and asset performance over time.
The Regulatory Pressure is Mounting
This issue is no longer confined to the engineering department. Local governments are stepping in. Municipalities across the country, like Denver, are imposing temporary moratoriums on new data centers and industrial construction due to power capacity and environmental fears. The regulatory frameworks emerging from these pauses will undoubtedly include strict energy efficiency requirements. The facilities that get permitted to build or expand in the future will be those that can definitively document responsible, asset level energy management.
At the same time, corporate sustainability commitments are hardening into strict compliance obligations. New financial climate disclosure rules, state-level energy reporting, and strict tenant service agreements all require granular asset data. An operator who cannot produce that level of detail is flying blind on their single largest operating cost.
The Human Element of Energy Resilience
Amid all the talk of artificial intelligence, automation and smart sensors, the industry frequently overlooks its most valuable asset. A trained maintenance technician is completely irreplaceable as the first line of defense in national energy resilience.
Software can flag an anomaly, and sensors can track an energy spike, but data alone never turned a wrench or optimized a failing cooling valve. It is the technician on the ground who translates digital insights into physical energy savings.
When maintenance teams are supported by effective maintenance and asset management systems, they shift from a reactive mindset to a proactive discipline. They can catch calibration drifts, replace degrading components before they become energy drains and ensure that every asset operates at its peak thermodynamic efficiency.
This human element is especially critical today. As a massive wave of experienced engineers approaches retirement, using a CMMS or EAM to capture their institutional knowledge and give the next generation a structured way to maintain these complex systems is paramount. If workforce execution drops, energy waste inevitably spikes.
Rethinking the AI Investment
The pressure to change is no longer just an internal goal. Local governments across the country are actively pausing new industrial and commercial projects out of sheer panic over grid capacity. The companies that will be permitted to operate, expand, and thrive in the future are those that can definitively document responsible, asset-level energy management.
At the same time, financial disclosure rules and corporate compliance mandates are hardening. Leaders are being asked to provide granular data on their operational footprint. An executive who cannot produce that data is flying blind on their single largest operating cost.
The conversation around America’s energy future must expand beyond the supply side. We cannot simply build our way out of this crisis with more power plants if we continue to allow preventable operational waste to drain the system from within.
By focusing heavily on supporting the technician workforce and instilling strict maintenance discipline, organizations can dramatically reduce unnecessary energy consumption. It is time for leadership to recognize that operational discipline, maintenance execution, and asset visibility are no longer secondary business functions. They are becoming essential components of energy resilience and long-term infrastructure stability.
Jason Penkethman is the chief product and technology officer of Limble. He brings extensive experience building and scaling high-performing product and engineering teams across global markets. He has a strong track record of driving product transformation, delivering customer-centric solutions, and aligning technology strategy with business growth.
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