AIOps reduces complexity and drives digital transformation, but it also offers additional advantages. Discover seven benefits of AIOps that can help transform your operations.
As organizations look to speed their digital transformation efforts, automating time-consuming, manual tasks is critical for IT teams. Therefore, many organizations are evaluating the benefits of AIOps.
Artificial intelligence for IT operations (AIOps) uses machine learning and AI to help teams manage the increasing size and complexity of IT environments through automation. However, its benefits go beyond increased automation and reduced complexity. There are seven AIOps benefits, in particular, that can transform your business operations.
But first, let’s start with a better understanding of what AIOps is, how it works, and its value to organizations.
What is AIOps, and how does it work?
AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. While these functions set the stage for AIOps adoption, they are not enough in isolation. A truly modern AIOps solution also serves the entire software development lifecycle to address the volume, velocity, and complexity of multicloud environments.
AIOps aims to provide actionable insight for IT teams that helps inform DevOps, CloudOps, SecOps, and other operational efforts. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing:
Many companies combine second-generation application performance management (APM) solutions to collect and aggregate data with machine-learning-based AIOps tools that add analysis and execution. But this approach introduces complexity and a potential loss of context. A modern, holistic AIOps platform, meanwhile, encompasses all four stages to deliver an end-to-end operational approach.
Seven benefits of AIOps for operational transformation
Along with reduced complexity, IT teams can transform their operations with seven key benefits of AIOps, including the following:
1. Improved time management and event prioritization
Given the sheer number of software services that organizations develop and use to improve operational processes and meet customer needs, it’s easy for teams to get bogged down in the details. These teams need to know what must be addressed right now and what can wait.
2. Reduced IT spend
Another AIOps benefit is it can also reduce operational costs. By proactively identifying potential issues, AIOps tools can alert analysts before they lead to a costly outage. A modern AIOps solution can also save teams considerable time and effort by eliminating false positives.
In fact, according to a Forrester Consulting report, implementing an AIOps approach that provides proactive visibility helped companies improve operational efficiency and reduce false-positive alerts by 95%. Additionally, research from Dynatrace found that implementing AIOps could save companies an average of $4.8 million per year by automating key processes.
3. Increased business innovation
The faster companies can respond to changing market conditions, the better. AIOps reduces the time and effort required to keep the lights on by automating key processes. This allows IT teams to focus on what matters — implementing strategic initiatives that drive business success.
For example, consider the adoption of a multicloud framework that enables companies to use best-fit clouds for important operational tasks. If IT teams spend the bulk of their time responding to alerts and dealing with false positives, there’s little time for innovation. By implementing AIOps, teams can free up developers to tackle new projects.
4. Expanded collaboration
AIOps solutions are naturally data- and department-agnostic, which helps organizations expand their collaboration efforts. As such, they ingest and analyze data from multiple sources to produce holistic outputs that aren’t tied to specific use cases or business teams. As a result, AIOps makes it possible for disparate departments to speak the same language and improve collaboration.
5. Streamlined product improvements
Once products and services are live, IT teams must continuously monitor and manage them. These teams need to know how services and software are performing, whether new features or functions are required, and if applications are secure.
Like the development and design phases, these applications generate massive data volumes that offer relevant and actionable insights. Such insights include whether the system can effectively collect, analyze, and report this data. Here, AIOps tools can pinpoint potential areas where teams can improve applications. An AIOps platform can also identify the most cost- and time-effective approaches to make these changes at scale.
6. Enhanced automation
Manual processes are time-consuming and error-prone. However, AIOps makes it possible to automate key tasks, such as error detection, alert analysis, and event reporting. This allows IT operations teams to shift their focus and prioritize outcomes, rather than sorting through initial observations to find relevant reports.
7. Accelerated digital transformation
According to the Dynatrace 2022 Global CIO Report, organizations are under more pressure than ever to keep pace with digital transformation. And efforts are well underway: The report states 99% of large organizations have now adopted a multicloud environment to improve business outcomes. However, 58% of IT leaders say infrastructure management drains resources as cloud use increases. And 56% say traditional monitoring solutions are no longer fit for purpose.
The result is a digital roadblock. For many organizations, adopting new technologies can add to management and monitoring challenges, which can slow the pace of transformation. Another benefit of AIOps tools is their ability to consume and analyze the ever-increasing amount of data. A comprehensive AIOps solution can help companies confidently adopt new digital technologies.
What are the business benefits of AIOps?
Of all the AIOps benefits, however, the ultimate advantage is its business value.
By automatically collecting, analyzing, and executing responses to issues, AIOps enables organizations to reduce overall complexity. But AIOps also improves metrics that matter to the bottom line. For example:
- Greater IT staff efficiency. With greater visibility into systems’ states and a single source of analytical truth, teams can collaborate more efficiently. More reliable, context-based analysis enables teams to make better decisions, take more decisive action, and automate more functions. With better data intelligence across the software development lifecycle, individuals in every role can exercise more autonomy and experience greater job satisfaction.
- The ability to preempt outages. By automating incident detection and response, teams can significantly reduce MTTR, which improves uptime. But a truly modern approach to AIOps can detect and fix issues before they become outages. Such an approach can conduct automatic business impact analysis to prioritize the issues that matter most to the business. This enables teams to work smarter, not harder.
- Improved user experiences. The bottom line for any business’s bottom line is a better user experience. Greater system reliability and uptime improve user experiences. But a modern approach to AIOps also provides real-time insight into digital experiences in context to what users are trying to accomplish. An AIOps platform that can visually replay user sessions to see specific struggles enables teams to better optimize user journeys.
- Maximum ROI on all hybrid cloud technologies. As cloud-native technologies evolve, organizations layer in more tools and open source solutions to solve specific problems and provide specific benefits. A platform approach to AIOps that provides observability and automatic analysis of all these technologies enables teams to optimize outcomes. With greater observability and contextual analysis, teams can maximize their return on investment (ROI) on all their hybrid cloud technologies.
Create a cloud observability strategy with automatic and intelligent AIOps
To realize the full benefits of AIOps, teams need to do more than simply adopt tools that use statistical, correlation-based machine learning. In practice, businesses are best served by adopting a deterministic, fault-tree AIOps platform that provides end-to-end visibility, observability, and accountability.
To learn more about how Dynatrace helps organizations transform faster — and more intelligently — with AIOps, read the eBook, “Developing an AIOps strategy for cloud observability.”