Finance organizations are rapidly deploying AI workloads to support fraud detection, risk modeling, customer service, and other high-performance applications. As GPU-based AI infrastructure expands, many IT teams are discovering that traditional power architectures were not designed to handle the rapid load fluctuations these workloads create.
Yet, with the rush to adopt AI workloads, many of these organizations are discovering that their existing IT infrastructure wasn’t built to support these demanding workloads. AI workloads create unpredictable power fluctuations that demand resilient, scalable power infrastructure. These rapid power swings can place significant stress on electrical equipment, accelerating wear, reducing reliability, and increasing the risk of failures across the power infrastructure. For banking institutions, insurers, accounting and investment firms, even brief power disruptions can interrupt transactions, impact customer service, and create regulatory risk. That’s why AI-tolerant 3-phase uninterruptible power supplies (UPSs) are becoming the first line of defense to handle substantial load increases and dynamic changes.
Understanding AI-driven power fluctuations
UPS systems must do more than provide backup power; they must continuously stabilize an increasingly dynamic electrical environment. AI workloads are unpredictable, triggering power surges in milliseconds that place significant stress on supporting equipment. AI training algorithms are executed in sync on the graphics processing units (GPUs) in the data center, resulting in an oscillating load profile.
The UPS absorbs these fluctuations first. If it can’t respond quickly enough, power instability or load drops can affect the critical applications that financial organizations depend on for real-time transaction processing, fraud prevention, customer interactions, and market operations. To prevent these interruptions, many are turning to AI-tolerant UPS. An AI-tolerant UPS is designed to absorb the sudden power spikes and drops created by AI workloads, helping keep critical applications running without disruption.
Validated under real AI workload conditions
Schneider Electric designs its UPS products to handle various site and application conditions, including the dramatic compute fluctuations of AI workloads. To that end, we’ve conducted rigorous load tests on our Galaxy V series UPSs, like the Galaxy VXL, designed specifically for demanding AI workloads.
The tests used load profiles of real hyperscale customers, so we didn’t rely on simulations. The tests showed that the Galaxy V Series UPS units handle fluctuations without load drops or performance issues. They use advanced double conversion and our patented eConversion topologies to handle the variability.
Tests were conducted at 40° Celsius ambient temperature and showed the UPSs comfortably supported loads of 1% to 100% with no limitations. Galaxy VXL, Galaxy VX, and Galaxy VL units also handled up to ten minutes of 125% overload, and one minute of overload at 150% load level. These results confirmed the robustness of the Galaxy V series for AI loads.
For financial institutions adopting AI, this level of resilience helps ensure that critical applications remain available even as compute demands fluctuate dramatically.
Why battery selection matters
The tests demonstrated that the type of battery the UPS uses makes a difference when supporting AI workloads. Frequent, dramatic fluctuations require fast discharge and charge rates for batteries.
Lithium-ion batteries outperform valve-regulated lead acid (VRLA) batteries when it comes to supporting the fluctuating demands of AI workloads. Especially above 110% load levels, VRLA batteries struggle with high-frequency load changes while lithium-ion batteries handle them seamlessly. This makes a critical difference for finance organizations deploying AI at scale. Beyond performance, lithium-ion batteries offer a longer lifespan than VRLA options—reducing maintenance needs and lowering total cost of ownership when paired with AI-ready UPS systems.
Preparing the entire power train for AI
While UPS performance is critical, AI readiness requires evaluating the entire electrical infrastructure. For finance organizations modernizing data center environments, AI infrastructure planning should focus on the resilience of the complete power chain—not just individual components. Switchgear, breakers, cabling, and battery systems should all be assessed to ensure they can accommodate rapid load fluctuations associated with GPU clusters.
The UPS should be integrated into a design and system that can handle dramatic fluctuations, including the switchgear, cabling, and circuit breakers. Schneider Electric offers end-to-end solutions for our customers’ needs in AI training and inference, including designing a robust power train.
Scaling AI infrastructure without overbuilding
Financial institutions rarely deploy AI as a single project. Rather than sizing for future AI demand on day one, financial organizations can deploy capacity incrementally as new models, customer service, and analytical capabilities are introduced. Modular UPS architecture allows infrastructure teams to match power investments with AI adoption timelines, reducing upfront capital expenditures while maintaining room for future growth.
UPS infrastructure should be scaled just as efficiently. UPSs such as the Galaxy VXL series offer parallel configuration options (n+0, n+1) to enhance redundancy and reliability, protecting AI workloads from power outages and load fluctuations.
With solutions like Galaxy VXL, operators don’t have to build full capacity from day one. Instead, they can leverage the solution’s modular, scalable architecture, which allows operators to add power modules as their needs grow.
Switching modules is also safer and easier with Schneider’s Live Swap capability, which lets technicians remove and add modules without shutting down the UPS unit. Live Swap is like changing a tire without having to stop the car.
Discover more – AI-tolerant UPSs support for finance organizations’ resilience
As AI becomes more embedded across finance organizations, resilient power infrastructure becomes a competitive advantage. The companies that succeed will be those that can scale AI without compromising the reliability and security that customers and regulators expect.
The Schneider load tests show that the Galaxy VXL, along with various other Galaxy V-series 3-phase UPS solutions, maintain stable power output despite the high fluctuations of AI workloads. This means our solutions support AI clusters, reducing the risk of AI power disruptions, and thanks to their built-in modularity and redundancy, Galaxy VXL UPSs allow finance institutions to add resilience, scalability, and future-proof operations.
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