It's hard to visit a tech website these days without reading an article about how artificial intelligence (AI) is poised to uproot entire industries and workflows. As it turns out, IT systems operations fall under the umbrella of things that are likely to change or already have due to AI. That shift created a new IT category called algorithmic IT operations -- or AIOps for short. The basic definition of AIOps is that it involves using artificial intelligence and machine learning to support all primary IT operations. The goal is to turn the data generated by IT systems platforms into meaningful insights.
Your message has been sent. There was an error emailing this page. IT operations has become the lifeblood of all businesses today. A healthy IT organization can provide key competitive advantages for businesses in a fast-paced market. Many companies struggle to meet the high demand due to increased cloud system complexity.
Organizations around the world are turning to technology to revolutionize their businesses. This requires a rethinking of the entire IT stack and operations strategy. In their 2019 report, Gartner lists several revolutionized technologies and delves into how those tools and solutions will challenge IT organizations from an operations and management standpoint. Though the underlying application and service delivery stack has gone through massive transformation with virtualization, the cloud, microservices, containers and more, even today, the primary IT operations tools organizations use are relatively old. Critical IT operations activities, such as migration, upgrades, patch management, capacity planning, service and change management are becoming extremely challenging due to the volume and varieties of data that exist across the IT stack.
As organizations venture into the brave new world of artificial intelligence (AI) in the enterprise, the first stop in the journey is in many cases the organization's own IT operations department. This trend is underscored in recent industry research. A study by Enterprise Strategy Group (ESG), for example, found that AI in IT is a common entry point into the use of AI and machine learning in the enterprise. In a survey of IT leaders, the firm determined that the top two use cases for AI were IT systems management-and-orchestration functions and IT system log file error analysis.1 The majority of the respondents in the ESG survey liked the idea of using AI as a recommendation engine, while a significant percentage of the remaining respondents wanted a system that can automatically detect, analyze, recommend and apply changes as needed.
Self-driving cars and medical advances may grab all the headlines, but artificial intelligence is being applied to any number of less high-profile applications across a variety of industries. Perhaps the most unsung and yet closest to home for IT organizations comes in the form of "AIOps." That could be because applying artificial intelligence to IT operations is still an emerging area, so it hasn't garnered much attention. But early indications are that this is a growing area. It's too small for the Magic Quadrant treatment at Gartner, but in August 2017, Gartner issued a Market Guide for AIOps platforms.