The IT landscape is a dynamic innovation space, powered by the emergence of the latest technologies. Enterprises must ensure that critical IT systems are efficient and high-performing. Companies are finding it hard to keep pace with the growing complexity of IT systems. Here’s where AIOps (Artificial Intelligence for IT Operations) can help enterprises manage incident alert volumes and slash monitoring and management costs.

The current solutions

The traditional solutions that enterprises have used over the years for monitoring ITOps are:

• Firms have hired CIOs/CTOs to improve the IT infrastructure and make sure all essential systems are running smoothly.

• Some firms have also hired system administrators to manually identify and report incidents within the IT framework.

• Some enterprises rely on customers to report an incident with their digital infrastructure.

However, the current practices are not feasible and cost more. AI for application monitoring aims to reduce the costs involved in hiring system administrators and other IT professionals.

How can AIOps help in cost optimization?

AIOps platforms automate the monitoring and incident reporting process. AIOps based analytics platforms will have financial benefits for your enterprise such as:

1. Higher uptime and ROI with AIOps

Too many incidents within the IT infrastructure can result in system failure. Some enterprises also fear capacity exhaustion that can affect essential IT operations. Since software systems are responsible for revenue-generating business processes, a low uptime will impact your services and customers may move to a competitor enterprise. Subsequently, high downtime directly impacts your ROI (Return on Investment). AIOps can help you increase your uptime and continuously provide services to customers. With higher uptime, your IT operations will keep generating revenue.

AIOps improve the uptime of software systems by the following means:

• AIOps enhances the observability in user experience and helps find and resolve incidents faster. MTTD (Mean Time to Detect) will decrease significantly with an AIOps based analytics platform.

• AIOps will help you develop a workflow automation software architecture. You can allocate business resources appropriately with AIOps.

2. Less investment in training and recruitment

AIOps will filter the noise in the alert systems and help IT teams can act accordingly. A reliable AIOps platform will also tell you the systematic steps required for fixing an incident. Since AIOps platforms remember the past incidents and provide actionable insights based on the historical incidents, they reduce pressure on IT teams to manually solve diverse incidents.

Many enterprises bring IT experts on an ad-hoc basis for solving incidents within the IT infrastructure. It not only increases the financial cost, but it also is not a permanent solution. AIOps can help you fix incidents faster with available resources.

3. Effective root cause analyses

How will you solve an incident if its root cause is not known? Software systems are getting complex and enterprises often must hire IT experts for root cause analysis. Once again, it increases the costs involved in fixing an incident within the IT framework. AIOps is an AI automated root cause analysis solution. Once the root cause is determined, an AIOps platform will inform you about which IT team is responsible for fixing the problem. You can fix the IT issue quickly if you know the source of the problem resulting in higher uptime and ROI.

4. Cost-optimization in the long run

One may debate over the high installation costs for AIOps adoption. Initially, you can try AIOps solutions for simpler IT processes to see immediate financial benefits. Besides revenue generation, AIOps platforms decrease the number of incidents within the IT framework. It also helps in avoiding situations like capacity exhaustion and IT outages that involve fixation charges. In the long run, AIOps can save considerable money for your organization.

AIOps platforms support predictive analytics for business forecasting. Predictive analytics uses historical data and predicts scenarios like capacity exhaustion and IT outages. It lets you take proactive steps to ensure that the issue never occurs.

An AIOps transformation translates into direct financial outcomes for a business:

• OPEX optimization: AIOps can highlight high operational costs and reduce them via automation. Organizations adopting AIOps can see a reduction in overall IT operational cost, by proactively monitoring, predicting, and remediating incidents and automating the entire process.

• TCO reduction: Technical outcomes like Root Cause Analysis, Noise suppression, and Prediction often translate in the reduction of capital expenses (Capex) for enterprises investing in AIOps tools.

In a nutshell

The AIOps industry has an impressive CAGR of 21.05%. The global AIOps industry size will be worth more than 40 billion USD by the end of 2026. Enterprises are leveraging the financial benefits of using AIOps for incident resolution and system monitoring. With AIOps, your essential systems will be up and running continuously. Higher uptime will ensure high service availability for your business. Adopting AI essentially means complete business transformation.