The benefits of using artificial intelligence for IT operations are many. By infusing artificial intelligence (AI) into IT operations, you can leverage the considerable power of natural language processing (NLP), big data, and machine learning (ML) models to automate and streamline operational workflows, and monitor event correlation and causality determination.

For today’s IT professionals, AIOps is also one of the fastest ways to realize tangible ROI from digital transformation investments. Automation is often centered on efforts to optimize spend, achieve greater operational efficiency and incorporate new and innovative technologies, which often translate into a better customer experience.

But where to start? In this blog post, we’ll look beyond the basics like root cause analysis and anomaly detection and examine six strategic use cases for AIOps. Plus, we have practical next steps to guide your AIOps journey.

1. Operationalize FinOps

Today, you have seemingly endless options on where your IT systems and applications live—in the cloud, on-prem and even on the edge. The appeal of this hybrid cloud strategy is that you can have all the resources you need to assure application performance. But “always-on” is costly, and too many organizations overprovision to mitigate performance risks (and overspend in the process).

To address this waste, consider implementing FinOps (Finance + DevOps). This cloud financial management practice is a way for cross-functional teams—like Engineering, Finance and Product—to work together and take ownership of cloud usage. AIOps helps you operationalize this approach by using data-driven cloud spend decisions to safely balance cost and performance. By using software—not people—you can take appropriate actions and give applications the resources they need when they need them. You’ll also build trustworthy automation for your IT teams since every action is backed by data. The result: reduced costs, less alert fatigue, less waste and documented ROI for your automation efforts.

Next steps:

• Start with a consulting perspective on FinOps and CIOs
• Read the Quick Guide to Operationalizing FinOps
• Explore how to operationalize FinOps with IBM Turbonomic

2. Create more sustainable IT

According to a study from the IBM Institute for Business Value, CEOs ranked sustainability as the top challenge—ahead of regulations, cyber risks and technology infrastructure. There are many ways to approach this challenge, but the more successful CEOs are leveraging their sustainability investments to optimize operations and embrace digital transformation—a win/win scenario that combines sustainability performance with better financial outcomes.

To meet your own sustainability challenges, start by optimizing your data center: data centers worldwide account for 1-1.5% of global electricity use. You can make an immediate impact by making data-driven decisions on application resource allocation. When applications consume only what they need to perform, you can increase utilization, reduce energy costs and carbon emissions, and achieve continuously efficient operations.

Next steps:

• Start with an overview of Green Computing
• Learn How Digital Technologies May Help Operationalize Sustainability for the CIO
• Read the paper: Accelerating FinOps & Sustainable IT

3. Improve CI/CD pipelines

The continuous integration/continuous delivery pipeline—commonly referred to as the CI/CD pipeline—is an agile DevOps workflow focused on a frequent and reliable software delivery process. It enables DevOps teams to write code, integrate it, run tests, deliver releases, and deploy changes to the software collaboratively and in real-time. A key characteristic of the CI/CD pipeline is the use of automation to ensure code quality.

As you consider ways to improve your IT systems, employing observability to create a high-performing CI/CD pipeline is an excellent use case for AIOps. Observability, powered by AI and automation, replaces older, more manually intensive performance monitoring tools. You gain full-stack visibility to better understand your environment and speed up innovation. You’ll also have automatic discovery, monitoring, and validation of the performance and integrity of applications in production, including your cloud infrastructure, virtual machines, container-based microservices, shared multi-tenant infrastructures, and storage systems—all reporting on metrics such as usage, availability, and response times.

Next steps:  

• Start by rethinking DevOps
• Get the Enterprise Guide to Observability
• Read the eBook: Leverage Automated APM to Accelerate CI/CD

4. Assure application performance

For many organizations, their applications are their business. Ensuring that those apps perform consistently and constantly—without overprovisioning and overspending—is a critical AIOps use case.

Like both FinOps and more sustainable IT, this use case embraces the idea that automation is key to optimizing cloud costs. That’s because IT teams, no matter how skilled they are, just don’t have the capacity to continuously determine the exact compute, storage and database configurations needed to deliver performance at the lowest cost. Software can identify when and how resources are used, and match actual demand in real-time. Like many AIOps use cases, you can start with baby steps and take non-disruptive, reversible actions that immediately lower costs, improve performance and build trust.

Next steps:

• Start by rethinking cloud operations
• See how legendary brand Carhartt achieved record holiday sales
• Explore cloud cost optimization with IBM Turbonomic

5. Strengthen end-to-end system resilience

Organizations are constantly looking to increase end-to-end IT system resilience to mitigate the risks associated with system failures, outages and downtime. By applying this AIOps use case, you can strengthen end-to-end IT resilience and ensure uninterrupted service availability.

By leveraging real-time root cause analysis capabilities powered by AI and intelligent automation, AIOps enables ITOps teams to swiftly identify the underlying causes of incidents and take immediate action to reduce both mean time to detect (MTTD) and mean time to resolve (MTTR) incidents. AIOps platform solutions consolidate data from multiple sources and correlate events into incidents, granting clear visibility into the entire IT environment through dynamic infrastructure visualizations, integrated AI capabilities and suggested remediation actions.

Using predictive IT management, your IT teams can leverage AI and machine learning algorithms to automate IT and network operations to resolve incidents swiftly and efficiently—and proactively prevent issues before they occur, enhance user experiences, cut costs, and drive business success.

Next steps:

• Start with What is incident management?
• Learn how to reduce MTTR

6. Eliminate tool sprawl

We’ve all been there—just when you’ve mastered one business tool, another comes along. In fact, 53% of organizations say their IT teams need to spend even more time managing technologies and infrastructure. This IT tool sprawl—multiple tools and applications across the IT environment—leads to complexity, inefficiency and increased management efforts.

For a more agile and streamlined incident management process and a better employee experience, the use case for AIOps tools is compelling. An AIOps platform gives you a holistic view of your IT operations and enables you to consolidate various IT tools into a centralized solution—a central pane of glass for monitoring and management. Leveraging AI and automation, an AIOps platform aggregates, correlates and analyzes vast amounts of data from various sources. It can also trigger notifications, alerts and remediation actions, and eliminate the fire drill of cross-discipline emergency meetings.

Next steps:

• Start with the basics of ITOM
• Get the Gartner Market Guide for AIOps platforms
• Learn how to accelerate IT incident remediation time with IBM AIOps Insights

Get started

If you’re looking for ways to infuse your operations with automation, you’re not alone. 97% of your fellow IT professionals believe that AI—when applied to IT operations—will deliver the type of actionable insights they need to help automate and enhance overall IT operations.

And while implementing all six use cases might be the dream, it’s important to note that applying even one can help you deliver digital transformation. You’ll be able to find and fix problems faster and more efficiently, boost employee productivity and deliver a better customer experience.

Explore IBM AIOps solutions and discover how AI and IT deliver the data-driven insights that IT leaders need to help drive exceptional business performance.

Learn more about IBM AIOps solutions