The current “standard operating procedure” in most companies’ IT operations is no longer tenable.
That’s a bold statement to make, but based on our work with hundreds of companies around the world, it rings true. The driving forces behind digital transformation now require traditional IT to evolve from a cost center to manage into a valued business asset that’s inextricably linked to a company’s brand, reputation and value delivered. Yet the IT organization is struggling to keep pace due to the business’s exploding complexity and accelerating innovation—and IT’s own operational shortcomings—one being that its staff cannot grow at the same rate as the complexity. IT leaders need a better way to manage their IT operations—and that better way is AIOps.
At a high level, Gartner defines AIOps or Artificial Intelligence for IT Operations as “platforms and software systems that combine big data and AI or machine learning functionality to enhance and partially replace a broad range of IT operations processes and tasks, including availability and performance monitoring, event correlation and analysis, IT service management, and automation.”
Today, the use of AIOps is rare. Only 5 percent of all large enterprises use analytics and machine learning in their IT operations functions (i.e., AIOps) to combine big data and machine learning functionality to enhance or optimize IT operations and automate processes and tasks. However, Gartner predicts that number to rise to 40 percent by 2022.1
Interest is growing in AIOps for good reason. Using AIOps to transform IT operations into a service-oriented model can provide a variety of real, tangible benefits, including deeper insight into the customer experience, cost optimization, risk mitigation, and an overall more-responsive IT organization.
1 "Market Guide for AIOps Platforms," Gartner, August 2017