What Is AIOps? Meaning, Examples, and Use Cases

Written by Coursera Staff • Updated on

As businesses undergo a digital transformation, so too do IT operations. Learn more about how AI and machine learning provide new solutions to help IT professionals do their jobs.

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Artificial Intelligence for IT Operations, or AIOps, pairs advanced analytics with IT operations. Businesses have become more reliant on digital technologies, resulting in more complex digital problems and an increased need for IT professionals prepared to deal with them using such modern techniques as AI and machine learning. 

In this article, you’ll learn more about what AIOps do, their real-world use, and their benefits to IT professionals and businesses. 

AIOps meaning and purpose

As noted above, AIOps stands for Artificial Intelligence for IT Operations

At its core, AIOps is all about leveraging advanced analytics tools like Artificial Intelligence (AI) and machine learning (ML) to automate IT tasks quickly and efficiently. Rather than replacing workers, IT professionals use AIOps to manage, track, and troubleshoot the increasingly complex problems associated with businesses’ widespread adoption of digital platforms and tools. 

For example, a survey conducted by McKinsey & Company states that businesses ‘accelerated the digitisation of their customer and supply-chain interactions and of their internal operations by three to four years’ during the COVID-19 pandemic [1]. As a result, businesses around the globe increasingly rely on digital technologies to run virtually every aspect of their operations, resulting in complex interactions between digital tools that must work properly for these organisations to function. 

AIOps provides a way for IT professionals to parse through the vast amounts of data produced by a business’ many digital platforms, resolve problems quickly, and (in some cases) design solutions before they even arise. 

AIOps example

As workplaces become more reliant on interdependent digital platforms connecting one department to another, the likelihood of a critical technical failure like system shutdowns increases. 

As a result, IT operations management must maintain a real-time view of how digital technologies function within a business. That could inundate the team with constant notifications that may conceal the most important problems within a wave of routine reports. To highlight only the most important notifications, AIOps can help monitor notifications and only flag critical issues to IT operations teams, ensuring that the most pressing problems get resolved swiftly. 

AIOps use cases 

Artificial intelligence can help IT professionals accomplish many essential tasks in their day-to-day work. Some common ways that AIOps solutions are used every day include: 

  • Anomaly detection. AIOps work to detect anomalies and flag them for relevant personnel. 

  • Root cause analysis. AI can assist in identifying the reason that a problem occurred.


  • Event correlation. Machine learning models efficiently scan large volumes of data and detect the most important events within them. 

  • Automated remediation. Automatic systems can solve some problems and troubleshoot them without human intervention. 

  • Performance modelling. AI is used to model performance and design potential solutions. 

  • Cohort analysis. User data is analysed to understand better when errors occur, why they occur, and how to fix them for improved performance. 

AIOps benefits

AIOps brings the power of artificial intelligence and machine learning to the IT domain, providing the latest cutting-edge tools used in advanced analytics today. In effect, AIOps allow IT professionals to perform descriptive, diagnostic, prescriptive, behavioural, and predictive analytics to improve their operations. 

Some of the benefits that businesses and IT professionals can expect include: 

  • Lower operational costs and increased ROI for IT solutions 

  • More efficient remediation due to intelligent monitoring tools 

  • Improved customer experience online resulting from improved digital systems 

  • Swifter service management due to AI capable of managing high-volume data sources 

  • Predictive modelling capable of identifying problems before they arise and assisting in the design of solutions to stop them from occurring 

AIOps tools and platforms 

Although the field is still new, many AIOps platforms and tools are available to both professionals and businesses today. Some popular platforms include: 

  • IBM Instana Observability. IBM Observability is an enterprise application performance monitoring tool with automation capabilities. It can be deployed on-premises or as a SaaS solution.

  • Cisco AppDynamics. AppDynamics is a full-stack app performance management tool. It uses analytics to measure application performance with key business metrics for deeper insights.

  • Datadog. Datadog specializes in observability for cloud-scale applications. It also offers AI capabilities and cross-team collaboration tools.

Learn more today

As the digital transformation of business operations accelerates, IT professionals (and the solutions they provide) become increasingly necessary for a business's day-to-day functioning. Prepare for your future in AIOps by taking an online, flexible course through Coursera today.  

For those just starting out, Google’s IT Support Professional Certificate prepares course takers for an entry-level position by teaching IT support tasks such as computer assembly, wireless networking, installing programs, and customer service. This course takes less than six months to complete and can give you a solid grounding in IT support and increase your understanding of AIOps. 

Article sources

  1. McKinsey & Company. “How COVID-19 has pushed companies over the technology tipping point—and transformed business forever, https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/how-covid-19-has-pushed-companies-over-the-technology-tipping-point-and-transformed-business-forever.” Accessed August 29, 2023.

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