Remember when the “cloud” was just a buzzword? 10 years ago, many people thought that cloud technology was overhyped. Now, the cloud is a given.
There’s a similar discussion about AIOps today. Once again, some people are skeptical. However, I predict that AIOps is destined to follow the cloud, with widespread adoption across industries. Organizations will quickly learn that they can’t remain competitive without AIOps. Just like the cloud, AIOps is going to rewire IT.
Just to make sure were on the same page, let’s define AIOps. AIOps stands for Artificial Intelligence for IT Operations, and it optimizes IT operations functions using machine learning and big data. That’s the opposite of how many IT operations departments work today, struggling with manual processes and heavily siloed tools that don’t share data.
Why is AIOps so important? Enabled by the cloud, businesses are digitizing at unprecedented speed. The pace and scale of change is staggering. And IT operations just can’t keep up. There’s just too much complexity and too much to manage. With SaaS apps and cloud services, business units are bypassing IT altogether—and this has been going on for years. AIOps changes this dynamic, ensuring that IT operations can run at digital speed and lead from the front.
With AIOps, your IT operations team doesn’t have to dig through thousands of events from siloed monitoring tools, spending hours correlating disconnected data to identify impacted services and the root cause of failures. Instead, they immediately see a small number of actionable alerts and impacted services on a single console. They also see appropriate historical and real-time context, including relevant incidents, problems and changes for affected CIs, providing valuable shortcuts to issue diagnosis and resolution. They can also see how similar issues were remediated in the past and can even remediate issues automatically. Taken together, these AIOps capabilities significantly lower MTTR, reduce the number of major incidents, and increase operational efficiency.
AIOps is ready for prime time. While the transformative promise of AI hasn’t materialized yet in many parts of the business, AIOps is different. It doesn’t need a staff of data scientists or AI translators. It doesn’t need a major reorganization like many other large-scale AI initiatives. In fact, AIOps is the perfect pilot for other organizational AI initiatives, building sponsorship beyond IT as it transforms IT operations—which in turn transforms the business.
Recently, Tomer Mekhty, ServiceNow’s VP of IT, talked about this point: “In IT operations, we’ve been using AIOps for some time to solve business problems. We’ve found that we don’t need to hire new data scientists to drive AIOps. Instead, we can rely on our existing data analysts and machine learning skill sets.”
Make no mistake: ServiceNow has seen great results with AIOps. For example, we used to have a huge number of VPN outages. Given our remote workforce around the world, this caused major employee frustration. Once we implemented AIOps, we reduced our VPN outages by 900 hours a year and reclaimed 1,000 hours in employee productivity—reducing lost time from 1,400 hours to just 400 hours.
So, what is the most important success factor when adopting AIOps? Tomer says it’s a change in mindset. He explains, “What we’ve found is that AIOps needs a cultural change. It’s really about organizational change management. You need to establish a data-driven culture where most decisions are based on data, not experience. And, leaders need to start asking the right questions to drive efficiency. You also need to develop your existing talent or replace skillsets manage the scale and demand.”
So, what are you waiting for? AIOps offers you a proven, pragmatic path to improved service quality, reduced service downtime, and vastly increased operational efficiency. Ultimately, that translates into sustainable business advantage as you run IT at digital speed.