AI is driving a surge in power demand, data center electricity use on track to double this decade. As that demand grows, grid construction in many regions now lags behind build schedules, leaving facilities finished before power is available.
The resulting delays and added costs have turned energy reliability into a board-level risk.
Yet many organizations still approach power as if it were guaranteed—an operational detail rather than a strategic dependency. When leaders plan for growth, they focus on technology investments, workforce expansion, or new markets. Power rarely gets the same attention, even though it underpins all three. That mindset stems from decades of stability in regulated energy markets, but that assumption no longer holds.
The growing mismatch between build timelines and power availability is already slowing growth.
Goldman Sachs forecasts a 165 percent increase in global data center demand by the end of the decade. In the United States, data centers already account for roughly 4 to 5 percent of total electricity use, and that number continues to climb. These workloads are putting additional strain not just on data centers but also on the communications and energy infrastructure beneath them. In major hubs such as Northern Virginia, Santa Clara, and Phoenix, McKinsey reports that it can take three years or more to secure new power capacity, creating a major barrier to deployment and growth.
This is not a temporary spike; it is already reshaping the economics of networks, data centers, and communications infrastructure.
Power is no longer just an operating expense. It’s a competitive differentiator for organizations that treat it as a strategic asset. Those that do gain clear advantages:
Downtime costs can reach more than $9,000 per minute in lost productivity and service disruption. For operators managing public safety communications, broadband networks, or other critical infrastructure, the stakes are even higher. The real cost isn’t measured only in dollars—it’s reflected in trust, service continuity, and sometimes even lives.
If power is now a competitive differentiator, the next question is how to manage it. The answer lies in moving from reactive to predictive power systems.
Traditional backup systems—diesel generators and basic batteries—were designed for a different era. They react to outages. But the AI era demands power systems that can anticipate demand, balance inputs, and optimize performance in real time.
Modern, battery-first architectures carry the immediate load on high-performance batteries, then draw from the grid, solar, wind, or a generator as needed. An intelligent controller manages those sources to minimize fuel use, noise, and wear. With integrated telemetry and analytics, predictive power systems can flag issues before they happen and schedule maintenance when it’s least disruptive and most cost-effective.
Predictive power means:
It’s the same transformation we’ve seen in IT: from reactive troubleshooting to proactive, analytics-driven operations. Power must evolve the same way.
Real-world deployments are already showing what this shift looks like in practice.
The lesson is clear: power strategy can’t be one-size-fits-all. It must align with each organization’s mission, environment, and risk profile.
These examples highlight what it takes to treat power as a true strategic asset. Doing so requires a shift in both mindset and management. Organizations can start by focusing on four key areas:
We often say that data is the new oil. But in reality, without power, data doesn’t move. Power is the foundation of digital transformation, and in the age of AI, it is one of the most strategic assets an organization controls.
The companies that thrive in this new era won’t just manage power, they’ll lead with it.