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Automation and orchestration have been a boon to the IT industry. The need for a unified platform to combine the disparate domains of IT and Service Management is becoming more apparent. AIOps integrates the management of IT systems, operations, and service desks into one coherent system that can be monitored in real-time. The AIOps market is expected to grow from an estimated $3.2 billion in 2017 to $6.4 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 12%. With this growth rate, it's no surprise that the IT Service Management/Service Desk space has been flooded with all sorts of solutions and companies offering their take on what constitutes "AIOps." It can be hard for organizations to know where to start when they're exploring how AIOps will work for them, especially because there are so many different opinions about what it should do. 

This blog post will help you navigate your way through the marketing hype and provide some guidance on getting started with the basic building blocks required before deploying.

What exactly is AIOps?

 AIOps is an acronym for artificial intelligence in information technology operations. It is a term that refers to the application of machine learning (ML), data science, and AI technologies to information technology operations problems with the goal of not just handling but harnessing the massive streaming datasets that are common in IT environments.

According to Gartner, AIOps platforms should be able to "consume and analyze the ever-increasing volume, variety, and velocity of data generated by IT and present it in a useful way." This advantageous method may imply the complete or partial replacement of manual operations such as ITSM, automation, availability and performance monitoring, and event correlation and analysis. Gartner also expects that by 2023, 30% of big companies would use AIOps and digital experience monitoring solutions exclusively to monitor applications and infrastructure, up from 5% in 2018.

AIOps in information technology service management (ITSM) and service desk environments

While AI has the potential to automate and enhance a wide range of business processes, ITSM environments are frequently overlooked in the race to AI. One factor could be our perception of ITSM. In theory, IT service management should support a broader variety of IT activities than service desk routines to improve alignment between ITSM and IT operations management (ITOM). In truth, ITSM efforts are excessively focused on end-user issues—the service desk.

Another reason AI may appear to overlook ITSM is that IT teams, and particularly service desk settings, sometimes struggle to automate minor, repeated operations. This implies they spend the majority of their time performing manual activities rather than tackling ITSM from a more macro, holistic perspective.

However, AIOps can eliminate this time waste by reducing service desk tickets by up to 85 percent. This enables service desk agents to focus more intently on the work that does come through (which has the added benefit of increasing job satisfaction, as they are not performing the same chores every day).

New AIOps technologies are focusing exclusively on these ITSM duties, enabling the automation of typical issues such as slow computers, user login failure, and printer and plug-and-play device failure. 

AIOps automation brings in several benefits:

• Reduced ticket volume
• Time spent on each ticket is reduced
• Quicker MTTR and MTBF
• Freed up time for IT workers to work on human-related issues
• Enhanced customer satisfaction
• The agility of the team increased

However, AIOps encompasses much more than automation. AIOps can assist service desks in transitioning from reactive to proactive problem management by leveraging the enormous datasets generated by ITSM teams. The most effective AIOps technologies should be capable of combining real-time and historical data to:

• Anticipate outages. AIOps can scan your whole monitoring dataset and then use machine learning methods to discover event patterns indicative of more serious problems. IT would then be notified of the probable issue.
• Establish a schedule of events. Through training on ITSM incident data, AIOps can forecast the business impact of a service event. This enables IT to prioritize events according to their context and business value.
• Analyze and ascertain the underlying reason. Using event patterns and service architectures, AIOps finds root causes of errors faster than humans can.

How to implement AIOps into ITSM

While you may be prepared to deploy AIOps solutions for your IT staff, your company's decision-makers may not be. 

Here are some pointers on how to get your IT department started with an AIOps initiative:

• Dive deep into the technologies. Even if AIOps adoption is not imminent, knowing AI, machine learning, and data science may help you make the case for when the time is right to dive in.
• Share your knowledge. Take your newly acquired expertise and share it with colleagues and executives using simplified tools and applications.
• Select test cases wisely. Implement AIOps on a small scale, analyze what worked and what didn't, and iterate from there.
• Identify gaps. Since skill and experience gaps are natural in emerging technologies, overcome concerns by identifying them and proposing solutions.
• Enhance the ITSM platform's modernization. A modern ITSM platform that supports AIOps should incorporate self-service, cost insights, process automation, and more into a single, consistent ITSM process record that leverages data to provide accurate real-time, end-to-end insights.
• Bring your ITSM and ITOM platforms into sync. Thus, workflows across IT, from ITSM to help and service desks to ITOps, may be unified.
• Deconstruct data silos. AIOps requires additional data, therefore dismantle siloed monitoring tools. The best should include a comprehensive feature set, pre-integrated tools, customization options, and an AIOps roadmap.
• Consider areas other than information technology. Once your data is secure and broadly available, you may use AIOps to acquire insight into cross-business unit issues.

Selecting the optimal AIOps tool for ITSM

Getting started with any tool can be challenging, but this is especially true when new technology and ways of thinking are involved. AIOps tools for ITSM are no exception. When selecting the appropriate AIOps technology, bear the following considerations in mind as you transition from AIOps theory to AIOps practice:

• Business requirements
• Prioritize your cases
• Sources of data that are currently available and those that will be added in the future
• Required skillsets
• Time to value.
• Integration with currently used tools
• Adoption ease, from installation and training through use and maintenance.
• Clarity and trust vs. a "black box" strategy
• Obtain practical assistance with AIOps

To keep up with the demands of digital transformation, IT operations teams must work quicker and smarter than ever before. Bayshore takes a pragmatic, real-world approach to examining how artificial intelligence may boost speed and efficiency. At Bayshore, AIOps is involved in every stage of our ITSM approach and we're embedding it into every piece of the modernization jigsaw.