If you are looking at transforming your IT operations team’s efficiency and effectiveness, you are looking for Artificial Intelligence for IT Operations (AIOps). Defined by Gartner as a platform that combines Big Data and AI functionalities to enhance the performance and management of IT operations processes and tasks, AIOps includes application of text analytics, advanced analytics, facial and image recognition, machine learning and natural language generation.

According to a report published by IDC a market research firm states that global spending on cognitive AI systems will reach $57.6 billion by 2021. Opportunities for AI enterprise is abundant, as they will turn millions of ideas into one masterpiece. AIOps solutions are expected to bring simplicity to the existing complex issues and deliver outcomes which are engaging and profitable, apart from being innovative and intelligent.

If you are looking at implementing AIOps for your organization, you must have come across numerous vendors offering all kinds of AI tools with the promise of transforming your IT operations overnight. It’s no doubt getting started with AIOps can be daunting, but it is best to take it to step by step.

Here are the four pillars of a successful AIOps implementation in your organization.

1. Define the objectives– The first step is to identify what AIOps can do to for your organization. What is it that your IT infrastructure needs help with which can be accomplished with AIOps. For instance, you might want AIOps to provide service availability through incident remediation or support your ITSM practice with alert escalation, suppression and de-duplication or be an add on to your DevOps program, to provide actionable insights through data modeling and analysis. The reason could be any but it is important to define it first in order to successfully implement it.
2. Set a success parameter – The parameters to measure the success of an AIOps implementation includes mean time to resolution (MTTR), prevention of outages, enhanced employee productivity and reduced costs as a result of automation and reduction of touch points. These benchmarks can help check on the level of implementation success.
3. Segment the data – It is important to segment the data in order to measure the success of implementation. To realize the full value from your investment on AIOps, you need to focus on organization-specific data and segment it accordingly.
4. Plan the data collection and analysis – The right data helps build the right insights. And therefore, collecting the right data needs a well thought-through plan. AIOps tools rely heavily on data to provide valuable insights and be effective. Therefore, to be able to make the most of AIOPs investment, it is advised to create a plan to collect the relevant data. The second part of the plan must include how to analyze the collected data.

Driving digital transformation with AIOps

Like every other digital platform AIOps is also a journey towards transformation and not the destination. Therefore, the successful implementation of AIOps opens many doors towards complete digital transformation. With assistance from machine learning and analytics, AIOps enables IT teams to focus more on addressing high-value information and support business operations to improve end-user experience, delivering significant business value.

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