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AIOps: Yet Another Acronym or a Real Transformational Technology for IT Operations?

Roy Illsley
Omdia

The introduction of the latest technology — such as AI and machine learning — can be seen as a way for organizations to accelerate growth, increase efficiency, and improve customer service. However, the truth is that the technology alone will do little to deliver on these business outcomes. AI for IT operations (AIOps) is one area where the application of technology, if not matched with organizational maturity readiness, will fail to deliver all the promised benefits.

Market Definition

The AIOps market has evolved from many different domain expert systems being developed to provide more holistic capabilities. The new report, Omdia Universe: Selecting an AIOps Solution, 2021–22, brings Omdia's vision of what an AIOps solution should currently deliver as well as areas we expect AIOps to evolve into.

AIOps is a term that has been adopted by the market to define the way IT operations needs to perform in digital enterprises. Omdia defines AIOps as the overarching technology that can bring all the management practices (observability, rapid mitigation, augmented decision making, self-healing, auto-scaling, etc.) in IT together. This concept does not translate to a single person or team that can now perform all these activities; rather, a single view can be obtained, and a single control point established. Omdia clarifies the sector by identifying the key characteristics of an AIOps solution.

The current reality of the market is that many different AIOps solutions exist, but they do not all deliver on Omdia's ten key characteristics. 

Omdia View

The IT department is going through a significant, and many would argue long overdue, transformation. At the heart of this transformation are the new emerging technologies such as AI, quantum computing, blockchain, etc.

The degree to which these technologies when deployed will deliver the desired business outcomes is less clear, and Omdia argues the outcomes are more closely linked to the maturity and culture of the organization, and matching that to the use of technology, than to the technology itself. IT operational activities (defined as those activities IT undertakes to ensure business users can perform their activities) span multiple different disciplines, yet most organizations still have a very team-centric, or domain-centric, approach to managing and orchestrating these disciplines.

The rise of DevOps was seen as the vehicle to bring two of these different disciplines together for the greater good in order to improve business outcomes faster. While it is true DevOps has gone some way toward changing the culture and mind-set of IT operational activities, it remains focused on a too-narrow definition of the role IT has to play in the digital enterprise.

Omdia considers that AIOps represents a natural evolution of DevOps and can become more inclusive of all the activities that impact the customer/employee experience, or business outcome. It is only when IT can ensure its focus is customer outcome-centric that its activities will be aligned to the business's objectives and the tools used will be used in a way designed to ensure it meets those objectives.

AIOps adds the missing link that can bring the disparate processes and tools together for the single purpose of delivering improved business outcomes, not just improving IT efficiency.

Recommendations for Enterprises

The adoption of new concepts that claim to be a silver bullet has traditionally failed to deliver fully on its promises. AIOps is no exception; it is not a shrink-wrapped solution that can simply be deployed in order to automatically generate an improvement in the performance of IT operations. Instead, it is the application of AI to the different activities IT performs.

By linking all these activities, sharing knowledge, and automating actions, AIOps can deliver. But this requires the IT department to be honest in terms of the current level of organizational maturity and what it can realistically expect to reach in the next 12 months by using AIOps. 

Omdia's AIOps Universe

Omdia is a proud advocate of the business benefits derived through technology, and AIOps is at the forefront of realizing benefits for IT operational teams. The Omdia Universe report is not intended to advocate an individual vendor, but rather to guide and inform the selection process to ensure all relevant options are considered and evaluated in an efficient manner. The report findings gravitate toward the customer's perspective and likely requirements, characteristically those of a medium-large multi-national enterprise (5,000+ employees).

Download the Omdia Universe Report

Roy Illsley is a Chief Analyst at Omdia

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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AIOps: Yet Another Acronym or a Real Transformational Technology for IT Operations?

Roy Illsley
Omdia

The introduction of the latest technology — such as AI and machine learning — can be seen as a way for organizations to accelerate growth, increase efficiency, and improve customer service. However, the truth is that the technology alone will do little to deliver on these business outcomes. AI for IT operations (AIOps) is one area where the application of technology, if not matched with organizational maturity readiness, will fail to deliver all the promised benefits.

Market Definition

The AIOps market has evolved from many different domain expert systems being developed to provide more holistic capabilities. The new report, Omdia Universe: Selecting an AIOps Solution, 2021–22, brings Omdia's vision of what an AIOps solution should currently deliver as well as areas we expect AIOps to evolve into.

AIOps is a term that has been adopted by the market to define the way IT operations needs to perform in digital enterprises. Omdia defines AIOps as the overarching technology that can bring all the management practices (observability, rapid mitigation, augmented decision making, self-healing, auto-scaling, etc.) in IT together. This concept does not translate to a single person or team that can now perform all these activities; rather, a single view can be obtained, and a single control point established. Omdia clarifies the sector by identifying the key characteristics of an AIOps solution.

The current reality of the market is that many different AIOps solutions exist, but they do not all deliver on Omdia's ten key characteristics. 

Omdia View

The IT department is going through a significant, and many would argue long overdue, transformation. At the heart of this transformation are the new emerging technologies such as AI, quantum computing, blockchain, etc.

The degree to which these technologies when deployed will deliver the desired business outcomes is less clear, and Omdia argues the outcomes are more closely linked to the maturity and culture of the organization, and matching that to the use of technology, than to the technology itself. IT operational activities (defined as those activities IT undertakes to ensure business users can perform their activities) span multiple different disciplines, yet most organizations still have a very team-centric, or domain-centric, approach to managing and orchestrating these disciplines.

The rise of DevOps was seen as the vehicle to bring two of these different disciplines together for the greater good in order to improve business outcomes faster. While it is true DevOps has gone some way toward changing the culture and mind-set of IT operational activities, it remains focused on a too-narrow definition of the role IT has to play in the digital enterprise.

Omdia considers that AIOps represents a natural evolution of DevOps and can become more inclusive of all the activities that impact the customer/employee experience, or business outcome. It is only when IT can ensure its focus is customer outcome-centric that its activities will be aligned to the business's objectives and the tools used will be used in a way designed to ensure it meets those objectives.

AIOps adds the missing link that can bring the disparate processes and tools together for the single purpose of delivering improved business outcomes, not just improving IT efficiency.

Recommendations for Enterprises

The adoption of new concepts that claim to be a silver bullet has traditionally failed to deliver fully on its promises. AIOps is no exception; it is not a shrink-wrapped solution that can simply be deployed in order to automatically generate an improvement in the performance of IT operations. Instead, it is the application of AI to the different activities IT performs.

By linking all these activities, sharing knowledge, and automating actions, AIOps can deliver. But this requires the IT department to be honest in terms of the current level of organizational maturity and what it can realistically expect to reach in the next 12 months by using AIOps. 

Omdia's AIOps Universe

Omdia is a proud advocate of the business benefits derived through technology, and AIOps is at the forefront of realizing benefits for IT operational teams. The Omdia Universe report is not intended to advocate an individual vendor, but rather to guide and inform the selection process to ensure all relevant options are considered and evaluated in an efficient manner. The report findings gravitate toward the customer's perspective and likely requirements, characteristically those of a medium-large multi-national enterprise (5,000+ employees).

Download the Omdia Universe Report

Roy Illsley is a Chief Analyst at Omdia

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...