The race to build new data center capacity is heating up, fueled by exploding demand for more advanced automation in business and everyday life. Enabling automation from agentic AI requires unprecedented capacity, availability and resiliency. As these autonomous agents are embedded into core business and personal processes, the underlying data centers are becoming more business critical and must be unfailingly reliable, whether hyperscale facilities, enterprise buildings, colocation sites or at the edge. When the data center is down, almost everything comes to a grinding halt.
In response to the data center race, the models for designing, constructing and operating AI factories are experiencing a profound transformation. Traditional manual “analog” processes are being phased out by highly advanced, comprehensive “digitally assisted” software -enabled processes. The days of engineers, contractors, project managers and operators working in silos with primitive and private tools are quickly fading.
Let’s look at how data center automation software is evolving to reduce design and build time with lower risk while optimizing operational performance and availability.
Design smarter with digital twins
For power systems, computer-aided design (CAD) software has been an electrical design staple. Now, cutting-edge software integrates into CAD can create detailed digital twin models. These models enable comprehensive analysis and simulation of the data center’s entire electrical infrastructure for things like short circuit analysis, load flow analysis, arc flash studies and energy usage.
Additionally, asset and planning software streamlines capacity planning, layouts and simulations for IT room layouts.
For cooling designs, digital twin software provides analysis of air and water flow, pressure and temperature, allowing for optimized energy consumption complemented with resiliency modeling through failure simulations.
Digitalize the building process
Digitalizing the build phase with software can provide advanced tendering and purchasing capabilities, as well as accurate schedule and budget management. Products can be specified using key parameters, including cost, availability, efficiency and embodied carbon. The software also provides a single place where the project is tracked, empowering all stakeholders to monitor any changes.
Automate operations
In this highest-of-stakes environment real-time control and coordination of critical power systems is essential. This includes on-site or adjacent sources including microgrids, along with back-up power systems including emergency generators, UPS, fuel cells and battery energy storage systems (BESS). Advanced analytics and AI models are used to optimize the power based on user preferences around availability, cost or carbon emissions. As the prime and backup power systems become increasingly complex, the role of software grows exponentially.
For cooling, software is leveraged to optimize performance and minimize power and water use. AI-enabled optimization software monitors air and water flow and temperature, making adjustments until the ideal settings are found. This software is especially important in larger data centers with thousands of cooling units and new AI factories with a combination of air-based cooling and liquid cooling. These software solutions are critical in AI factories where power and thermal management must be tightly controlled for optimal performance.
Resiliency through predictive maintenance
For power systems, the maintain phase relies heavily on predictive analytics using real-time and historical data to forecast potential failures, optimize maintenance schedules and reduce the risk of downtime. For example, the software can analyze the temperature of a transformer that is rising and schedule its replacement date, seamlessly coordinating the delivery, downtime and installation.
In the IT room, software can raise alarms of potential problems well in advance, predicting when critical thresholds may be exceeded. This capability is especially important in AI factories where there is no buffer because power and cooling typically operate at their capacity.
Cooling requires the most maintenance attention in the data center. AI software is now being leveraged to determine filter replacement and coil cleaning schedules in addition to longer term fan and motor replacement timelines. With the rise in liquid cooling systems and high-density cooling, intelligent software is becoming essential l to conducting water quality assessments and recommending fluid treatments.
For all of the domains, software is being leveraged to determine condition-based maintenance schedules as opposed to calendar-based maintenance, lowering costs and improving availability.
From digital twins to predictive maintenance: software’s expanding role
New and evolving data center software is central to the new era of data center development and operation. It accelerates design, enhances operations, ensures precise maintenance and drives sustainable performance. Software enables you to build digital designs before constructing in the physical world and run simulations to find the best possible approach. Software digitalizes the build process to improve resource efficiency, allowing you to save time, costs and energy, as well as pick sustainable materials. It provides greater visibility into all IT assets and enables control to automate power and cooling to optimize performance and sustainability. With software, you can streamline maintenance and repairs to automate asset lifecycle management. These innovations are especially valuable as data centers increasingly adopt AI workloads, edge computing and sustainability goals.
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