Impact of AIOps

The fact that the world is facing disruption with digital technology is palpable especially with the onset of artificial intelligence (AI). Businesses are striving constantly to keep up with the change of culture, change in role of network professionals and inception of new methods of operation. Market research suggests, approximately 40% of businesses that adopted advanced analytics lack adequate skills to optimize its utility. With the ongoing changes in the world of ITOps, emergence of new skills is evident. The impact AIOps will have in the role change of ITOps is immense and new IT skill sets will be required with a change in the role of ITOps since, it enables the IT department to integrate the general workloads with the emerging technology. Infact if we look at market research, enterprises are facing trillions of events data from logs, agents and network wire per day.

Preparing for AIOps

With an intention to provide improved service and efficient operation process, AI is deployed to manipulate big data including both, IT data and business data. AIOps can do both, automatically suggest a response or execute an appropriate response. IT professionals need to adopt new IT skills to deal with automation that AIOps brought with itself replacing the traditional ITOps. Infact, the largest barrier to adoption of AI is the lack of skills along with other challenges like company culture, infrastructure and data challenges.        

Traditional vs new IT skill sets

The deployment of AIOps is substantial not only in terms of technology, but also from a standpoint of process, culture and skills. AIOps is expected to produce a big change in ITOps’ role in both the data processing and the business as a whole. Let’s now try to analyze the traditional IT skills that were pre-existing and their transformation along with AIOps.

The traditional IT skill set was focused on data analysis for design, production and management to deliver services according to expectations. The focus is more on consistency and creating a stable environment for application and service. Traditional ITOps tools use manual expertise like human domain knowledge to execute tasks. Infact for traditional ITOps, a professional needs to set standards beyond which monitoring will be required, but in AIOps environment, a baseline is created by machines to set standards in case a certain level is attained, an automatic alert will be generated.

However, with AI at work, the IT professionals need to upgrade their skillsets to be able to audit and manage machine learning processes efficiently. AIOps will ensure the integration of IT infrastructure through ESM efforts across organizations. There is a considerable improvement in monitoring systems output, job logs and syslogs along with ticketing, incident and event recording system data. Also, AIOps uses supervised learning where the system is trained using sample data that leverages expected results. The new skillsets enable IT environments to anticipate and proactively manage AI to deal with issues along with responsibility of managing applications and migrating from the traditional to new ITOps like the SaaS apps. Infact, market research suggests that 74% of IT professionals urges for a proactive approach to performance monitoring. ITOps professionals are now aware and skilled to handle security issues. AIOps requires cross-domain communication skills to drive strategic approach. The skills required is more of practical working knowledge such as machine learning, knowledge about security alerts, application programming and algorithm. All these skills are essential to adopt AIOps in full swing.

Onset of AIOps

Although AIOps is extremely beneficial however, it is not independent as to operate on its own. Despite automation, skilled workforce remains an integral part of ITOps. The way in which algorithms handle the network, will have a direct impact upon overall business performance. So, a mere pattern recognition is not sufficient. Hence the IT professionals dealing with AIOps require training to supervise machine learning, and through which the IT team can stay informed about the network performance.

Inevitable – future of AIOps

Organizations adopting AIOps are rapidly experiencing reduction in system alerts by 90% and auto remediation for a successful business continuity. The following is the inevitable scope for the adoption of AIOps across different industries:

  • Financial organizations adopt AIOps to cater to high volume of trading systems.
  • Telecom service providers are adopting AIOps to successfully integrate 5G operations.
  • Both manufacturing and pharmaceutical companies are in the process of implementing AIOps in their operations.
  • AI-enabled automation bring visible changes in IT operations and IT job roles through automation of event response. Hence outages are better handled, improving customer impacts.
  • AIOps has made capacity optimization possible through clouds and on-premises systems.

Conclusion

As predicted by Gartner, the adoption of AIOps will increase by 30% in 2023. We can conclude that for AIOps to operate effectively, IT professionals need to understand the algorithms, access data and unify applications and services. This enabled automation of mundane tasks and IT professionals now can handle much bigger responsibilities to retain the machines and infrastructure of the business, running along with other value driven projects. Along with training IT professionals, third-party professionals or applications are often hired to meet the growing expectation.