Today’s IT ecosystem has increased in the complexity of application architectures and IT operations, and AIOps is the answer to such complexities. It can help identify root causes and identify anomalies in the network, predict upcoming faults and build intelligent correlations. The widespread adoption of AIOps by enterprises of all sizes has become imperative to enhance their infrastructure, operations, and cloud management.
AIOps offers predictive and service analytics, a unified dashboard, automated workflows, root cause analysis, etc. According to Gartner, 30 % of large enterprises will be using AI for IT operations (AIOps) platforms and digital experience monitoring technology to monitor their IT by 2023, from 2% in 2018.
AIOps helps accelerate innovation leading to quick decisions, faster iterations, and bringing hyper-automation into enterprises. The pandemic has undoubtedly played a role in bringing hyper-automation into the market as it fuels automation initiatives prioritizing digital transformation over all else.
What is hyper-automation?
Hyper-automation takes automation to the next level, making it digital process automation. According to Gartner, enterprises identify and automate as many processes as possible, involving a combination of tools and technology, with packaged software, ML, and automation tools to empower service delivery. It means that AI tools are used in combination with RPA to automate all repetitive tasks fast and augment human capabilities efficiently. Bots enable hyper-automation to further automation capabilities using several interoperable technologies, such as AI, RPA, analytics, etc.
Hyper-automation accelerates digital transformation and helps build digital resilience. It is a natural progression from AIOps, enabling the creation of a digital replica of physical assets and business processes. Hyper-automation offers real-time intelligence to understand the way different processes and functions interact and how they can be leveraged to drive business growth. Moreover, digital replicas provide actionable insights into IT systems’ health and performance, with AIOps playing a key role in hyper-automation.
Businesses experience higher agility and scalability when AIOps meets hyper-automation and are empowered to become autonomous digital enterprises. Troubleshooting performance issues are cut down by at least 50% with AIOps, and with our business ecosystem working in a distributed manner, hyper-automation transforms legacy infrastructure and repetitive processes enabling streamlined operations, leading to lower operations costs and a stronger position in the market.
While simple task-based automation has been a catalyst, it does not bring cross-functional results for better decision-making and business profitability. However, hyper-automation can do more as it transforms the enterprise by automating as many tasks as necessary.
Hyper-automation use cases
System health and performance
System monitoring is crucial to stay ahead of potential issues and remediation. It ensures that the system’s health and performance are maintained for optimum efficiency. While using automation has been useful in removing manual and tedious work, hyper-automation takes it a few steps further. It enables documentation of the workflows for the future and provides reports in real-time. It also enables data-driven decisions and saves time and may eliminate the need for escalation.
Data analytics in the customer service industry
The voluminous data recovered from several frameworks get manually transferred costing time that can be better spent addressing custom grievances. AI is used to collect data on call quality and for prioritization based on their significance. However, hyper-automation uses advanced analytics, RPA, AI, etc. together to deliver data analytics to enable swift decision-making.
Is there a difference between automation and hyper-automation?
The main difference between automation and hyper-automation is the difference between automating repetitive tasks removing human intervention on a small scale, and using multiple automation tools enabling intelligent automation, with ML, RPA, and taking automation initiatives up a few levels. This evolution is huge when bringing advanced automation tools into your enterprise as it is a game changer. It will ensure that your enterprise remains a strong contender in today’s Industry 4.0
According to Gartner, “organizations that automate 70+% of their network change activities will reduce outages by at least 50% and deliver services 50% faster.”