If you’ve been in IT for a while, you’ve seen some technologies come and go, without delivering any material impact. Have you ever wondered if AIOps is one of them? Well there’s good news. Organizations are achieving very significant benefits from AIOps today.

In this post, we will look at the challenges driving the need for AIOps, what some analysts have to say, and some key use cases that offer opportunities for harnessing its benefits.

Too much data: Operations teams can’t keep up

Today, business success is contingent on the optimized performance and continued innovation of IT-powered services. At the same time, the IT landscape continues to experience agile, fast-paced innovation and change.

With the proliferation of DevOps, the importance of real-time monitoring and observability is critical to the success of today’s accelerated development cycles. Combined with the rapid adoption of dynamic, cloud-native applications, data volumes have exploded, leaving Operations teams unable to process and manage this exponential growth. Therefore, the struggle to optimize service levels while enabling innovation continues to grow both more critical and more difficult.

According to Gartner, IT infrastructure and applications generate two to three times more data volumes every year.

To compound matters, tool sprawl has been hampering efficiency and productivity across many organizations. On average, Operations teams are using 11 different monitoring tools, which causes overlapping capabilities, promotes overspending, and higher maintenance costs. Additionally, IT teams face the following issues:

• Event noise drowns out real issues, reducing efficiency and increasing MTTR
• Problems go undetected until users and customers encounter problems
• It takes too long to resolve issues, putting SLA compliance at risk
• Struggling to keep pace, IT teams are ill-equipped to support innovation and instead must devote highly-skilled resources on non-strategic tasks, such as maintenance

The Promise of AIOps

To address the pressing and proliferating challenges outlined above, many organizations are looking to adopt artificial intelligence for IT Operations, or AIOps. AIOps equips Operations with a combination of machine learning, analytics, anomaly detection, and automation to realize enhanced efficiencies, cost savings, and speed across their organizations. With AIOps, teams can find and fix problems faster, and even gain the predictive insights they need to prevent issues from occurring in the first place.

Given the enormous potential of AIOps, the topic continues to gain increasing coverage by media and analysts. For example, in a recent report, IDC analysts predicted that by the end of next year, 70% of CIOs will aggressively apply AIOps to cut costs, improve IT agility, and accelerate innovation.