The Business Impact of AIOps and Observability

An opinion piece by the general manager of IBM Automation

Dinesh Nirmal

July 12, 2022

4 Min Read

IT workers are essential to keeping the internet − as well as the applications we use to manage our lives − running, but companies are struggling to identify talent and hire these employees at the pace they need. And while it is true that labor shortages are affecting many industries right now, there are numerous reasons why the problem is more acute in IT.

Not only is demand growing, but many of the most talented workers are beginning to retire, creating a crunch from both sides. Cloud computing was the number one most in-demand skill in June, according to the job placement site Indeed. Not only does the shortage of IT workers affect employers in almost every industry who need to keep their digital infrastructures running, it also puts people’s access to sometimes essential services at risk if they crash.

It is little wonder, then, that IT operations is one of the most popular applications for AI-powered automation, known in the industry as AI Operations or AIOps. In fact, a third of companies are now using AI to help improve and automate IT operations, the most popular use case across any industry, according to recent IBM data.

The reason is simple: The emerging trend of bringing together AIOps and observability can have a major impact on an organization's bottom line. With observability, which provides deep visibility into applications, and AIOps, businesses can more easily make sense of all the data coming in about their systems and better correlate it using AI. A recent Forrester study of businesses across banking, retail, telco, manufacturing and more found that it can reduce customer facing outages by up to 50% and mean time to recovery (MTTR) by up to 95%.

There are a few reasons why AIOps and observability together quickly yield such a large business impact, both by helping IT workers ensure programs work as they should through incident avoidance and incident resolution, but also by freeing those workers up to focus on higher value improvements and innovations.

Optimizing human labor

A key benefit of AIOps is that it frees up workers from low value tasks so they can focus on higher value ones. Some companies are not even dealing with a skills shortage, but they are simply growing at such a fast pace they cannot hire the right skills quickly enough. While a lot of the work a network administrator or IT worker does is strategic and planning-oriented, some of it is routine, for example manually intervening to increase application workloads if demand is spiking for some reason or reducing them to prevent wasted resources. AIOps and observability can automatically detect these demand spikes and adjust workloads based on demand, allowing your best IT talent to focus on the parts of their job that are more specialized and impactful.

Removing complexity

Another main driver of value is that automation of IT operations removes numerous layers of complexity that is inherent in managing massive amounts of data. You do not need to worry about delegation and staffing when the data from these data lakes is translated into actionable insights through AIOps and observability.  Employees have time to invest in making processes simpler, clearer and more effective, leading to greater optimization and driving cost savings.

Driving predictability

Beyond addressing talent shortages and cost savings, AIOps together with observability unlocks a lot of its value by allowing you to make better predictions, which has huge implications in a field that is largely about issue avoidance and issue resolution. Organizations that use AI and automation for their IT operations are better able to more deeply understand how applications and systems are performing in order to prevent outages, which create costs, reduce productivity and lead to negative publicity and backlash. When one service is hit, AI can help us understand why and look for related incidents by studying incident similarity. When we understand why problems happen, we can fix them much more quickly and, most importantly, work toward preventing them from happening in the first place.

Chief information officers and the people who support enterprise IT operations can have a thankless job, indeed they are much more likely to be noticed and criticized when something goes wrong as opposed to the things they do right.

At the same time, they are at the forefront of one of the most important labor trends today, the augmentation of human capacity by working with AI. IT workers are more likely than any other type of worker to be using AI today to analyze data, make predictions about the future, and automate tasks they used to have to do manually. In that way, they are driving immense value for their enterprises, by reducing costs, more deeply understanding how applications and systems are performing and preventing problems, but also innovating better processes to use in the future.

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