Rehlko has published an eBook on power infrastructure for AI-driven data centres, arguing that operators should assess AI readiness by how power systems perform under variable real-world loads, not by installed capacity alone. The publication examines the effect of large language models and other AI applications on data centre energy demand, particularly in environments built around graphics processing units. Data centre operators are under pressure to add AI capacity while utility connections in many markets remain constrained, and AI computing loads can fluctuate sharply and persist for long periods, creating operating conditions that differ from conventional workloads. This shift affects the design and operation of generators, alternators, battery systems and uninterruptible power supply architecture, requiring assessment of system stability, power quality, redundancy planning and battery cycling. Brian Melka, President and Chief Executive Officer of Rehlko, said traditional critical power design is being challenged by these new load profiles. "For decades, power infrastructure was designed around capacity and redundancy. AI introduces a fundamentally different operating reality," he said. "Rehlko is optimizing its products and redefining AI readiness as the ability to maintain stability, control and performance under continuous dynamic loads with five nines reliability." Rehlko says it works with customers from initial design through ongoing operation, covering power generation, controls, energy storage integration, distributed energy systems and modular infrastructure, framing this around energy resilience. Options highlighted include on-site gas generation, combined heat and power systems, battery energy storage, generator backup and modular power infrastructure delivered through its e-POD