The AI Boom’s Hidden Energy Toll
AI’s rapid growth and the surge in AI energy demand aren’t just transforming the way we work, innovate, and interact. It’s redefining the foundations of our digital infrastructure. From large language models to real-time generative applications, today’s AI systems require immense amounts of power, connectivity, and uptime. Behind the scenes, this is driving major shifts in how data centers are designed and exposing a critical gap in energy resilience.
The electric grid is already under pressure in many regions, and AI is accelerating that trend. For workloads like model training and inference, even brief interruptions aren’t acceptable. That puts backup power systems in the spotlight. No longer a supporting player, backup power infrastructure is becoming a critical component of digital continuity. That means thinking beyond the grid, and planning for power architectures that can withstand volatility, scale on demand, and recover instantly.
At the center of that strategy are diesel generators: still the most trusted line of defense in emergencies. But today, they’re part of a broader conversation, one that includes fuel flexibility, smarter controls, and complementary systems designed to ensure uptime in a high-stakes, AI-driven world.
The Escalating Energy Demands of AI
AI workloads are uniquely power-hungry, and AI energy demand is quickly becoming one of the most pressing infrastructure challenges of our time. According to the International Energy Agency, global electricity demand from data centers, AI, and cryptocurrency mining could double by 2026, reaching more than 1,000 terawatt-hours, roughly equivalent to the electricity consumption of Japan.
Training a single large model, such as OpenAI’s GPT-3, consumed an estimated 1,287 megawatt-hours of electricity; enough to power the average U.S. household for over 120 years. This kind of persistent load is reshaping how organizations think about power strategy. It’s no longer enough to ensure backup systems exist. They need to be faster, cleaner, and more intelligent.
Where Diesel Fits in a Changing Energy Landscape
Diesel generators have long been the backbone of emergency power in mission-critical environments, and they continue to be the most dependable option for fast, large-scale backup when the grid falters.
But as energy demands grow and regulatory scrutiny sharpens, operators are navigating new considerations. In some regions, emissions policies are beginning to shape how diesel systems are deployed, particularly outside of emergency use. At the same time, organizations are under pressure to meet ambitious ESG targets, prompting a closer look at fuel types, operational flexibility, and carbon reporting.
Still, diesel remains unmatched in its ability to deliver immediate, scalable power when it’s needed most. Rather than being phased out, it’s increasingly being supported by adjacent technologies, whether it’s cleaner fuels like HVO, intelligent controllers for optimized run-time, or integration with storage and grid-tied systems.
The result is a more adaptive architecture that reinforces diesel’s core role, while allowing operators to meet resilience goals without compromising on sustainability or compliance.
A New Era of Sustainable Backup
Fortunately, alternative solutions are gaining traction. Hydrotreated vegetable oil (HVO) offers one of the easiest paths forward, delivering up to 90% lower lifecycle carbon emissions compared to fossil diesel with minimal equipment changes. Hydrogen-powered generators are entering pilot stages in regions where supportive infrastructure exists. Battery energy storage systems (BESS) are being deployed for quiet, zero-emission resilience. Modular microgrids are enabling more dynamic control over power sources, combining renewables, storage, and backup systems.
These options come with tradeoffs around cost, availability, and scalability. But momentum is building. The battery energy storage market, for example, is expected to grow from $11.5 billion in 2022 to $49 billion by 2030, driven in part by the increasing adoption of data centers. At Rehlko, we’ve seen customers pilot HVO and hybrid configurations as part of future-ready infrastructure planning.
In Europe, some leading operators have already begun transitioning their backup generators to run on hydrotreated vegetable oil (HVO), achieving significant emissions reductions without modifying existing engine infrastructure. In parallel, U.S.-based operators are piloting hybrid designs that integrate battery energy storage with intelligent control systems to reduce generator runtime and emissions. These aren’t one-offs; they reflect a shift in mindset across the industry. Resilience and sustainability are no longer seen as competing priorities. Increasingly, they’re being engineered together.
What was once a binary choice between grid and diesel is becoming a layered, strategic approach to energy resilience.
AI, Meet Energy Optimization
AI is driving demand, but it’s also helping solve the very challenges it creates.
Across the energy sector, AI tools are optimizing grid performance, predicting energy needs, and reducing unplanned downtime. Grid operators using AI-based forecasting and load-balancing have improved power allocation efficiency by up to 20% during peak demand. Within facilities, predictive analytics and intelligent maintenance systems extend equipment life and orchestrate smoother transitions between battery, generator, and grid power.
When deployed thoughtfully, AI can help facilities meet performance and sustainability goals simultaneously.
Shared Responsibility, Shared Opportunity
Meeting the demands of AI at scale requires a broad coalition of stakeholders, hyperscalers, OEMs, data center operators, utilities, and policymakers. Collaboration is already underway. In Europe, the Climate Neutral Data Centre Pact is aligning operators with sustainability standards. In the U.S., the Department of Energy is modeling how AI-driven infrastructure will interact with an evolving grid.
But the work is just beginning. We need shared data, open frameworks, and long-term investment in sustainable energy resilience. Backup power must be part of that conversation.
One of the missing pieces in today’s backup power conversation is consistent reporting. While many operators track overall emissions, there’s little visibility into the carbon footprint of backup systems specifically, including generator runtime, fuel type, and emissions under load. As AI continues to attract scrutiny across the digital supply chain, standardized metrics for backup performance and sustainability will be key. Clear benchmarks can drive innovation, shape procurement decisions, and accelerate the shift to lower-carbon alternatives. Industry groups have an opportunity to lead, not just by setting decarbonization goals, but by defining how progress is measured.
Powering AI Responsibly
AI is reshaping the world. But behind every breakthrough lies a practical truth: it all depends on power.
As AI energy demand surges, backup systems can no longer be an afterthought. They must evolve into future-ready infrastructure that keeps pace with innovation.
