What You Must Know About the 5 Levels of AIOps Maturity

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In this special guest feature, Sean McDermott, CEO and founder of Windward Consulting Group and RedMonocle, offers what enterprises need to know about the five levels of AIOps maturity. Prior to Windward and RedMonocle, Sean was the Founder and CEO of RealOps, Inc., a pioneer in enterprise management Run Book Automation solutions which was acquired by BMC. Before starting Windward, Sean held senior positions with Predictive Systems and Booz Allen Hamilton.

As many enterprises look for ways to scale operations and improve customer satisfaction, one area proving its value is artificial intelligence for IT operations or AIOps. According to Gartner, 40% of organizations are expected to strategically implement an AIOps platform to enhance performance monitoring by 2022, and the AIOps Exchange found that 84% of IT leaders are budgeting for upcoming AIOps projects.

That said, AIOps shouldn’t be treated as another automation tool enterprises tack onto their tools portfolio but rather as a holistic strategy. As IT teams work to establish and continuously evaluate an AIOps strategy, they must start with the vision for long-term success. From there, the focus should shift to developing a foundation that identifies how to track progress and deploys machine learning and automation to create value and transparency enterprise-wide.

As an industry executive with nearly two decades of firsthand experience, I encourage organizations to begin their AIOps journey by first evaluating the possibilities and capabilities through the lens of five different levels of AIOps maturity. This approach helps achieve the full promise of a completely automated system and sophisticated operations with a strategic approach.

Let’s look at what enterprises need to know about the five levels of AIOps maturity:

#1 Reactive

At the reactive stage, events and logs are collected only for reactive purposes. Teams attempt to push through siloed operations with little to no communication with the rest of the business. This stage often leads to constantly extinguishing fires to keep operations up and running and to ensure customer satisfaction. Not only does the reactive stage prevent IT teams from showcasing their value to the rest of the business, but it also leaves them stuck in an endless state of solving issues rather than producing proactive strategy.

#2 Integrated

As organizations move into the integrated level, operational silos begin to deteriorate, and dialogue between the organization and IT teams are frequent and productive. Within the integrated phase, data sources weave into a unified architecture, and ITSM processes make strides towards improvement. In addition, artificial intelligence and machine learning start to layer into the process.

#3 Analytical

At the third level of AIOps maturity, more artificial intelligence and machine learning capabilities result in dramatic improvement. Data transparency is created among all stakeholders and across the enterprise, while teams establish more defined baseline metrics. As data becomes available, metrics become more measurable through the use of AI and ML, which expands the opportunity for IT teams to support AIOps and prove business value.

#4 Prescriptive

At the prescriptive level, teams implement ML and automation to provide access to more analytics and data to follow continuous improvements. This phase also involves a more optimized approach to ITSM processes.

#5 Automated

The fifth and final level of AIOps maturity is full automation with no human interaction. Teams leverage ML through prescriptive models, which provides complete transparency across all business levels. This final level gives teams the opportunity to play a more strategic role in business operations, while automation completes tasks in the background.

When maneuvering through each level, keep the long-term AIOps strategy and goals at the center to achieve the true potential of AIOps. By taking the process one step at a time, organizations achieve maximum performance for long-term success.

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