Like many of the digital transformations we’ve seen in the past few years, artificial intelligence (AI) is changing the way we all do business – including in data centers.

An increasingly used term that describes the method of using “machine logic” to solve very complicated problems for humans, artificial intelligence also describes the ability for a machine to “learn” similar to the way human beings learn. Software algorithms (programming, more specifically) develop relationships between large sets of data, then repeat the same function using the same algorithms, but including the “learning factor.”

The reason we’re hearing so much about artificial intelligence is because it’s one of the fastest-growing sectors in technology today. Artificial intelligence uses are expected to increase by 63% between last year (2016) and 2022; the prediction is a $16.6 billion market that’s driven by technology companies like IBM, Intel and Microsoft.

According to Siemens, there are specific artificial intelligence uses that are expected to grow between 2019 and 2024:

  • Autonomous robots (self-driving cars): 31%
  • Digital assistants (Siri-like automated online assistants): 30%
  • Neurocomputers (machines that recognize patterns and relationships): 22%
  • Embedded systems (machine monitoring and control): 19%
  • Expert systems (medical diagnosis and the smart grid): 12%

Artificial intelligence uses in data centers are also expected to increase. AI can help data centers reduce energy consumption and operating costs while improving uptime and maintaining high levels of performance. Need a few examples? Let’s take a closer look.

9 Tips to Improve System UptimeHow is AI Used in Data Centers?

Today’s data center owners and operators can take advantage of artificial intelligence uses in many different ways. For example, AI is already being used to:

  • Optimize server compute and storage systems
  • Improve uptime
  • Optimize cooling capacity
  • Reduce energy use
  • Optimize allocation of technical personnel
  • Reduce equipment hotspots
  • Support predictive analytics
  • Reduce risk

Off-the-shelf data center infrastructure management (DCIM) platforms can also be embedded with AI systems to reduce and control data center operating expenses. 

Vigilent, a company that uses IoT, machine learning and prescriptive analytics in mission-critical environments, reduces data center cooling capacity by employing real-time monitoring and machine language software to match cooling needs with the exact cooling capacity. This frees up stranded capacity; the “learning” side provides predictive analytics to determine when cooling infrastructure is at risk of failure. All of this results in uptime improvement, preventing unexpected downtime and revenue loss.

AI is also being used by hyperscale technology giants that have resources to fund AI R&D projects to optimize data center operations. Google, for example, joined the data center AI party when it purchased an AI startup (DeepMind Technologies) in 2014 to improve operating efficiency and reduce operating costs across its data centers.

Implementing a custom AI DCIM solution, Google has reduced overall data center power utilization by 15%, and reduced cooling power usage by approximately 40%. Machine learning controls approximately 120 Google data center variables, from fan speeds to windows. By taking a close look at temperature and pump speed data collected by sensors among server racks, artificial intelligence determined the best settings to create the most efficient environment possible.

The Future of Artificial Intelligence Uses in Data Centers

IoT systems, self-driving cars and social media are doing more than changing the way we work. They’re producing data that can be used to make decisions, save money and improve processes. Artificial intelligence uses this data in all types of settings – including data centers – to advance operations.

It won’t be long before DCIM systems will routinely contain an AI tool that not only optimizes critical mechanical and electrical equipment performance, but also optimizes compute and storage needs. AI will affect how data center operations teams work and change what’s involved with day-to-day tasks like fulfilling normal maintenance needs and monitoring networks. They’ll become “automation engineers,” using the AI engine to optimize data centers.

Belden provides data center solutions that can help your data center support increasing data demands, faster deployment, reduced costs, improved uptime and customization. To learn more about how we can help you prepare for what’s ahead, contact us!