Strategic AIOps Use Cases for IT Operations

Artificial Intelligence for IT Operations (AIOps) is a term that research firm Gartner coined. It refers to machine learning technology that facilitates IT operations analytics. According to The Insight Partners, the AIOps platform market size is expected to expand due to the expanding range of AIOps use cases from $2.83 billion in 2021 to a whopping $19.93 billion by 2028. The research firm adds that the market is poised to grow at a compound annual growth rate of 32.2% from 2021 to 2028.

In this article, we explore strategic and widespread AIOps use cases that are followed with the future application of AIOps and additional resources.

Understanding AIOps

AIOps platform combines human intelligence with automated algorithms, explains The Insight Partners. This offers users thorough visibility into IT system performance. The adoption of AIOps platforms is primarily driven by the need for companies to achieve agility and speed in the IT environment. Modern artificial intelligence and machine learning algorithms assemble critical and large volumes of data collected in the background and offer actionable insights.

Another noteworthy reason for the increasing adoption of AIOps solutions is the COVID-19 pandemic which resulted in work-from-home orders that required companies to rely more on tech.

But what does this mean for your company’s IT and DevOps teams? Keep reading to learn more about AIOps technology and eight AIOps use cases focusing on crucial benefits you can look forward to in your digital transformation journey.

Application of AIOps for IT

AIOps involves applying machine learning and analytics to big data to enhance and automate IT operations. AI can automatically assess huge amounts of machine and network data in real-time for anomaly detection and to locate patterns that can, one, perform the root cause analysis of existing issues and, two, predict and block issues in the future. So, AI is a technology your company’s IT department will want to leverage to minimize incident response time.

Again, Gartner first coined the term AIOps. The research firm described AIOps platforms as software systems that bring together AI or machine learning capabilities with big data to enhance and to a degree replace a wide array of IT operations tasks and processes. This includes performance monitoring, availability monitoring, IT service automation, IT service management, event analysis, and event correlation.

For instance, In India, with over 700 million internet users, the adoption of AIOps is vital for managing the growing demands on data centers. This technology not only automates troubleshooting, reducing repair times significantly but also improves network security by proactively identifying potential vulnerabilities. As India gears up for future expansions, including 45 new data centers by 2025, AIOps stands as a key driver in optimizing operations and supporting the country’s digital transformation.

Additionally, ITOM (IT operations management) has become increasingly challenging in today’s environment where the threat landscape is fierce. And that threat landscape isn’t static–it’s ever-evolving, so IT departments can’t afford to sit still. AIOps is designed to bring the accuracy and speed of AI to IT operations. Using traditional operations management solutions and processes, your IT team will find it a gargantuan task to keep up with the massive volumes of data streaming in from a variety of sources within network environments. AIOps can help in various essential ways:

Additional Resources on AIOps

Strategic Use Case of AIOps for Monitoring and Observability

Observability is a key part of leveraging AIOps for monitoring which is crucial for IT organizations to fully understand their systems, workloads, and processes. It involves ensuring system data, including metrics, logs, and tracing, is visible and trackable in terms of availability and performance.

This observability must cover various environments, whether on-premises, cloud-based, or within microservices. Recent developments have led to the emergence of AI Observability, which integrates monitoring of metrics, applications, and logs into one system. The concept of Unified Observability has become important, focusing not just on monitoring data sets but also on correlating them and placing them in context with each other.

AIOps uses this comprehensive observability to filter irrelevant data, providing early warnings of potential issues before they escalate and helping to proactively prevent failures. AIOps enhance observability and automation, supporting complex IT environments and enabling more proactive, strategic IT operations. The upcoming chapters will further define AIOps, its key features, and its impact on business, including steps for implementing an AIOps initiative.

AIOps for Enhancing Data Collection and Analysis

I. Streamlines Data Analysis

When you get the right AIOps platform for your company, you’ll instantly have a better way to collect the increasing flow of big data from various sources. Because of the power of AI, the platform will then automatically analyze the repository of data to predict and safeguard against future problems and figure out the cause of present problems.

II. Assemble Data from Various Sources

Yesteryear’s processes, solutions, and technologies weren’t designed to deal with the volume and type of data that is part and parcel of today’s digital era. Big data is a concept your company’s current monitoring tools might not be able to handle. Using yesterday’s approaches to deal with today’s big data reality consolidates the data and compromises data fidelity. Enter AIOps. An AIOps captures massive data sets of all types while ensuring data fidelity for thorough analysis.

8 Key AIOps Use Cases

After gaining a better grasp of what AIOps entails, it makes sense to consider the use cases.

1. Eradicates Business Service Impact

In today’s environment, it’s not enough to know whether or not business services are up and running or down and out. Your company needs to understand the degree to which everything is performing or underperforming and the availability, health, and status of different business and IT services. Obtaining the depth and level of insight needed to provide the answers is expensive and complicated if you rely on legacy monitoring solutions.

These solutions are inadequate because they provide piecemeal coverage. How do you address this issue? Enter AIOps. You can get past the above-mentioned challenges by using an AIOps platform.

2. Makes Data Analysis Easier

Is your IT department inundated with massive amounts of data in a dizzying array of formats? It can be challenging to stay on top of things using legacy systems not designed to handle the volume and velocity of data common today. To make informed strategic business decisions, you need access to reliable information. But if you don’t have a way to analyze big data, you’ll be at a disadvantage.

Using an AIOps platform, you’ll be able to rest knowing that the data is automatically analyzed to predict and safeguard against future problems. But that’s not where it ends because an AIOps platform will allow you to determine the cause of existing problems. What good is having access to a lot of information if you cannot derive value from it?

Leveraging an AIOps platform will ensure your IT team won’t find big data to be nothing but a big problem.

3. Get Rid of Application Blind Spots

You’d better hope it’s a planned outage if there’s an application outage. Your company may need to schedule some downtime for routine maintenance, for instance, and your application might not be available for an extended period. In such cases, you’ll want to alert your customers ahead of time so they’re not caught off guard.

The other type of downtime, the unexpected and unplanned kind, is where you will run into problems. An application outage might go undetected for a while if your company uses legacy tools to monitor such occurrences. This will create application blind spots that you can’t afford to overlook.

Fixing this problem will require your IT team to understand which application components depend on what infrastructure and how all the components or pieces interact. If this scenario is something you’ve encountered at your company, consider an AIOps platform. Such a solution will give you the tools you need to obtain the insight required to avoid blind spots.

4. Get a Handle on the Cloud

As of 2022, north of 60% of all corporate data is stored in the cloud. Reported benefits include, but are not limited to, lower IT costs, scalability, and business continuity. But one of the problems that many companies experience when they enter the cloud is sprawl. In other words, many businesses are working with multiple cloud providers to meet their different requirements.

What this sprawl issue is doing is increasing complexity and costs. If your company faces this problem, you’ll be at a time, productivity, and money disadvantage. One way you can turn things around and get a better handle on your cloud strategy is by using an AIOps platform. It’ll give your company’s IT team the visibility required to get all the benefits you want from the cloud.

5. Use Your CMDB Better

Another use case for AIOps is better use of your business’ configuration management database (CMDB) with AI Discovery. Your company’s CMDB requires accurate information entered in a timely fashion. But it’s not as easy as it appears to update a CMDB properly. And if you don’t have an up-to-date CMDB, automation is a moot point. Using AIOps can make your CMDB more useful.

6. Facilitate Event Correlation

Yet another AIOps use case involves event correlation. Your IT team is bombarded with a tidal wave of alerts, but the reality is that only a small percentage of them are critically important. You can count on an AIOps platform to find the critical alerts, assemble them leveraging inference modes, and figure out the main reasons for the problem. So, your IT team won’t have to sort through an endless stream of alert emails and experience alert fatigue–most of which don’t require their involvement. They’ll instead get the critical alerts that require their quick and decisive action. If you have a small IT team, you’ll be able to maximize their efforts by prioritizing high-level tasks.

IT department teams traditionally comb through infrastructure data to determine and fix problems. But AIOps has the ability to figure out the root cause of issues. It can tap into infrastructure alerts and direct them to the IT team via AP integration pathways. By so doing, AIOps tools facilitate incident auto-remediation by connecting IT operation management solutions with ITSM (IT service management) departments.

7. Threat Detection

Threat detection is a must. Using an AIOps tool, your IT department can fortify your security strategy. The tool will diligently search through the massive amounts of data to find any scripts, botnets, or other online threats that can critically damage your corporate infrastructure. Remember that AIOps platforms use AI and machine learning to uncover patterns that can jeopardize customer experience and business service availability.

8. Capacity Optimization

Capacity optimization is yet another beneficial use case for AIOps. With an acclaimed platform like Aisera, a recognized leader in the 2023 Forrester Wave AIOps Report, your AIOps can effectively keep track of raw utilization, memory, CPU, bandwidth, and other essential metrics. This capability allows you to maximize the usage of your existing capacity.

Future AIOps Use Cases

Reestablishing Human Oversight Amidst Data Deluge

AIOps is on the brink of transforming IT management by automating the analysis and prioritization of vast data volumes, allowing IT teams to focus on critical insights and decisions. By leveraging AI to filter out irrelevant data, professionals can dedicate their attention to strategic initiatives, ensuring that their expertise is applied where it’s most impactful.

This approach not only streamlines operations but also enhances the quality of decision-making, making the overwhelming data deluge manageable and actionable.

Accelerated Incident Response with Intelligent Alerts

Integrating AIOps into IT operations revolutionizes incident response with smart, actionable alerts that provide all necessary details upfront. This ensures rapid and accurate issue resolution, minimizing downtime. By learning from past incidents, these intelligent systems continuously improve, predicting potential problems before they escalate.

The result is a more resilient IT environment, where teams can swiftly address issues, keeping systems running smoothly and supporting business continuity.

Prioritization of IT Tasks Based on Business Impact Analysis

AIOps redefines task prioritization by analyzing the broader business impact of IT operations, ensuring that efforts are aligned with key business objectives. This strategic approach leverages machine learning to understand the implications of various tasks on user experience and revenue, guiding teams to focus on areas with the highest business value.

It marks a shift towards a strategic IT operations model, where decisions are made not just on technical urgencies but on their potential to drive business success.


If your company is in the market for an AIOps platform, such a tool can provide significant aid to your IT department. However, before making a selection, it’s important to weigh your options carefully, bearing in mind your specific requirements.

Aisera provides the AIOps functionality you are searching for. But don’t just take our word for it – consult with our AI & automation experts today and request a tailored AI demo for your enterprise!