What Is AIOps? Meaning, Examples, and Use Cases

Artificial intelligence for IT operations (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 (ML). 

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

AIOps meaning and purpose

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.

According to a survey by McKinsey & Company, 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 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 provide a way for IT professionals to parse through the vast amounts of data produced by a business’ many digital platforms, resolve problems quickly, and design solutions before they even arise.

AI capabilities

Artificial intelligence has a wide range of capabilities that open up a variety of impactful real-world applications. Some of the most common include pattern recognition, predictive modeling, automation, object recognition, and personalization. In some cases, advanced AI can even power self-driving cars or play complex games like chess or Go.

Consider starting your own machine-learning project to gain deeper insight into the field.

AIOps example

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

As a result, IT operations management must maintain a real-time view of how digital technologies function within a business, resulting in constant notifications that conceal the most important problems within a wave of routine reports. AIOps can monitor notifications and only flag the most critical issues to IT operations teams, ensuring the swift resolution of the most pressing problems.

AIOps use cases 

AI can help IT professionals accomplish many essential tasks in their day-to-day work. Some common ways 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.

• Automated remediation. Some problems are solved by automatic systems that 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, and how to fix them for improved performance. 

AIOps benefits

AIOps brings the power of AI and ML to the IT domain, providing the most cutting-edge tools used in advanced analytics today. AIOps allows IT professionals to perform descriptive, diagnostic, prescriptive, behavioural, and predictive analytics to improve their operations. 

Some 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 can identify problems before they arise and assist in the design of solutions to stop them from occurring 

AIOps tools and platforms 

Although the field is new, many AIOps platforms and tools are available to professionals and businesses today. Some popular platforms include IBM Instana Observability and AppDynamics.

Learn more today

As the digital transformation of business operations accelerates, IT professionals and their solutions become increasingly crucial 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, 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. Google also offers the Google Data Analytics Professional Certificate to prepare you for a career in data analytics.