What Is AIOps? Meaning, Examples, and Use Cases

Written by Coursera • Updated on

As businesses undergo a digital transformation, so too does 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, how they’re used in the real world, and the benefits they provide both 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 the widespread adoption of digital platforms and tools by businesses. 

For example, according to a survey conducted by McKinsey & Company, businesses “accelerated the digitization 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 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 organizations 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 are functioning within a business, resulting in constant notifications that can conceal the most important problems within a wave of routine reports. To highlight only the most important notifications, AIOps can be used to monitor notifications and only flag the most important issues to IT operations teams, ensuring that the most pressing problems are resolved swiftly. 

AIOps use cases 

Artificial intelligence can help IT professionals accomplish many important 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. Some problems are solved by automatic systems that troubleshoot them without human intervention. 

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

  • Cohort analysis. User data is analyzed to understand better when errors occur, why they occur, and how they can be fixed for improved performance. 

AIOps benefits

AIOps brings the power of artificial intelligence and machine learning to the IT domain, providing the most cutting-edge tools used in advanced analytics today. In effect, AIOps allow IT professionals to perform descriptive, diagnostic, prescriptive, behavioral, 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 modeling 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, there are many AIOps platforms and tools available to both professionals and businesses today. Some of the most popular platforms include: 

  • IBM Instana Observability 

  • Cisco AppDynamics

  • Datadog

  • LogicMonitor 

  • Moogsoft 

Learn more today

As the digital transformation of business operations accelerates, IT professionals (and the solutions they provide) become increasingly important to 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 such IT support tasks as computer assembly, wireless networking, installing programs, and customer service. AI visionary Andrew Ng’s Machine Learning Specialization, meanwhile, offers an overview of fundamental AI concepts and teaches practical machine learning skills in a beginner-friendly, 3-course program. 

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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 2, 2022.

Written by Coursera • Updated on

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