Adoption Barriers for AIOps

1. Blog 3: Opsramp.com Adoption Barriers for AIOps What is AIOps? AIOps is the application of machine learning and data science to IT operations problems. They combine big data and machine learning to enhance IT operations functions. Thanks to the ever- increasing data volumes and IT complexity, AIOps platforms are growing rapidly and are getting wider acceptance. ‘Infoholic Research’ predicts that the AIOps market is expected to reach approximately $14 billion by 2024, with a CAGR growth of 33.08% between 2018–2024. Gartner reports that by 2022, 40% of large enterprises will use AIOps tools to support or replace monitoring and service desk tasks. However, despite the proven benefits, there is still considerable skepticism regarding AIOps and AIOps projects. Let us have a look at the barriers to AIOps adoption. Barriers to AIOps Adoption The process of integrating AI with IT operations is complex and needs expertise. It requires significant data management capabilities and a culture shift. Here are some of the prominent barriers to AIOps adoption: 1.Data Quality Quality of data is key to AIOps success as it affects the accuracy of machine learning technologies. This is a challenge, however, because data is fragmented and stuck in silos in most organizations. Analytics depends on accurate data and when it is broken, the results are not trustworthy. 2.Existing Processes When it comes to new operations strategies, IT professionals may expect AI to help them maintain existing processes but save money and time. AIOps however is a fundamental reshaping and realigning of IT Ops. Hence, there is always a resistance to move away from time-tested traditional processes and enter a completely unchartered territory. 3.Executive Buy-In AIOps is not a tactical maneuver to solve temporary snags. It is a wider strategy and requires approval, buy-in and an evangelical push at the IT executive level for it to succeed. These leaders should spend time educating their organizations on why the investment is critical and the business value and efficiency that the solution can bring.

2. Blog 3: Opsramp.com Most AIOps projects fail when there is indifference at the leadership level. 4.Culture Shift Implementing AIOps requires a fundamental culture shift. Employees who are insecure about AIOps or other modern approaches taking away their jobs will resist it by being indifferent with the projects, not upskilling themselves, and creating cliques within themselves to oppose its implementation. 5.Skills Shortage Traditions IT operations skills focus on ensuring consistent, stable environments for service and application delivery. These tasks depend a lot on human intervention and knowledge to function smoothly. AIOps however is primarily about eliminating redundant, routine tasks, which helps IT professionals focus more on strategic initiatives which directly affect business outcomes. IT operators will need to gain expertise in data science and data analysis along with automation. The skills gap is AI is considerable and is one of the reasons why there is still resistance to adoption Conclusion The resistance to AIOps differs from organization to organization. The first step to break the barrier is to accept the inevitability of AI becoming integral to IT operations and understand its role and value. The key to succeed will begin with determining the ultimate objective of the project – whether to automate repetitive tasks, reduce waste orenhance customer experience. Once the goal is established, start with small processes that you want to improve and observe the results. Once the implementation is successful, celebrate successes to build momentum and evangelize AIOps.