The Need for AI to
Assist IT Operations and Management
COVID-19 has been a change agent for business IT. Technology has been at the centre of business discussion as companies move quickly to ensure business continuity while governments order shutdowns to slow the spread of the virus. Through the process, companies become more aware than ever that they need agility and speed to deal with a crisis; and technology plays a pivotal role.
New technologies and tools have been deployed in a very short timeframe, while some projects have been fast-tracked to meet the immediate needs. The measures put in place during COVID- 19 are likely to stay, since they deliver business benefits. Moreover, organizations are also likely to accelerate their digital transformation post-COVID to become more efficient and resilient.
IT services providers and technology vendors have been advocating the use of digital solutions (e.g., cloud, AI/ML, automation and IoT) to improve business processes and become more competitive.
Enterprises want to be more data-driven, and new systems deployed will generate a huge volume of data that will have to be analyzed for business insights. It becomes unmanageable for IT staff without the proper tools. Moreover, as businesses deploy more digital capabilities, it becomes more difficult to monitor
application performance across different environments. This is particularly the case since companies need to maintain legacy applications while building new ones – typically through the microservices model to accelerate the speed and frequency of upgrades. The complexity is also increased as companies adopt a multi-cloud strategy, including public cloud (e.g., AWS, Azure and Google Cloud) and private cloud (VMware-based) to better handle the complexities.
IT service management (ITSM) and IT operations management (ITOM) have seen a fair share of innovation. For service providers and organizations with sizeable IT estates or customer bases in particular, automation and the use of AI are crucial to better handle the volume of requests.
The term ‘AIOps’ is increasingly being used to highlight the need for more AI capabilities to reduce human intervention, both for delivering better business outcomes and to drive workforce productivity. AIOps can enable IT to better manage distributed environments across infrastructure, applications and services.
Some of the major use cases include predictive maintenance; identifying, troubleshooting and isolating faults; improving response times and remediation; and a data-driven approach to root cause analysis.