How AI is used in the data center

AI tools often gather and analyze data — processes that cannot be done manually or take too long to process. This enables admins to take preventative action before problems arise and optimize operations.

AI power management

Combining an AI tool with an advanced distribution management system can help facility owners and admins reduce power costs and environmental impacts. The advanced distribution management system prioritizes the power utility choice based on factors like lowest cost and carbon source. The AI tool then analyzes power usage in real time and automates the relevant power selection.

AI cooling control

AI learning models help optimize cooling options across wider uses as they monitor and analyze more data points than traditional cooling systems. For example, the partnership between Trane Technologies and BrainBox AI enables facility owners to automatically control cooling based on various factors, like weather, as well as schedules and sequences. BrainBox AI automatically analyzes the data and predicts each area’s thermal behavior to ensure adequate cooling.

AI network optimization

Looking beyond the traditional analysis and predictive workload distribution, AI tools can combine with data center infrastructure management (DCIM) applications to enhance network optimization. Some AI tools, like Juniper Networks’ Mist AI, automate the setup and configuration of new resources, such as virtual servers. This frees up admins to work on other tasks.

AI hardware maintenance

Monitoring the lifecycle of thousands of pieces of hardware in a data center is daunting. Add an AI tool to the mix to improve maintenance processes. AI analyzes all the data available in the facility to predict when intervention is necessary. Put DCIM, IoT sensor and equipment data into the AI application for analysis and notification of equipment like uninterruptible power supply (UPS) batteries, motors and servers.

AI security

AI tools can analyze a data center’s location and suggest improvements based on physical hazards, like flooding, fires or electrical damage. They can recommend steps to protect equipment or people from harm, like installing fire-resistant enclosures for UPS batteries. Use AI tools in the facility design phase or when new private networks are set up for clients of colocation data centers.

AI provisioning and configuration management

AI-powered apps can automate the setup and configuration of data center resources, like VMs and network settings. Admins can enable this through predetermined rules and policies for standard setups, configurations and workload needs, which saves time and reduces chance of errors.

Tasks needed to integrate AI into the data center

Enhancing data center operations with AI tools and apps requires research and planning. Here are a few ideas admins should consider before they deploy AI in the data center.

Identify AI goals and uses

As with any new strategy or operational tool, it is crucial to define specific goals and uses for an AI-based deployment in the data center. Admins should consider their plans and ask themselves: Are we looking to monitor and optimize energy usage and consumption, or do we want help allocating and provisioning resources?

Address data security

AI tools need to be given a lot of data to train and learn. Because of this, admins will want to ensure tight controls on that data to avoid breaches and privacy risks. Consider using synthetic data that mimics the real-world data the tool would use in production. Ask data security questions of any potential vendor to ensure they meet admin and customer requirements.

Research vendors and applications

Not all AI tools are compatible with a data center or align with specific uses. Admins must research AI tools to see how they align with their needs. Look for vendors with experience building AI tools for specific situations.

Start small and expand slowly

Applying AI throughout a data center can be a long and expensive process. Even deploying simple AI tools can cost hundreds of thousands of dollars and take months to train. Earning high ROI takes time. So, start small, and expand slowly. Each new implementation or usage is more straightforward and delivers faster ROI.

Planning for the future of AI in the data center

As AI tools and usage evolve globally, data center admins and owners must prepare for the future. They need to consider the use of more AI tools to manage and operate the facility as customer AI usage grows. Manual processes and 100% human intervention falls short of processing large amounts of data.

Admins must stay up to date on the latest AI tools that could help them manage operations. They need to test tools that meet their requirements, deploy new ones that automate processes better and always monitor them to ensure they are working as intended.

For data centers powering AI workloads for customers, they can redesign configurations to maximize performance. AI tools help design modern data centers, identify areas for improvement and monitor workflows.

AI-related training will become a large part of data center admins’ schedules, and that does not just include how to understand AI algorithms. Admins and other staff need to stay up to date on AI technologies and how to support them. Facilities that offer strong training programs will attract the best people and retain them longer.

Julia Borgini is a freelance technical copywriter and content marketing strategist who helps B2B technology companies publish valuable content.