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ServiceOps: ITSM and ITOps Move from Cooperation to Collaboration

Valerie O'Connell
EMA

Nothing drives IT change like … change. There has been plenty of that to go around in the past few years. Planned digital transformation initiatives turbocharged into accelerated implementation as employees working from anywhere raised the stakes of day-to-day IT operations to business-critical levels.

Complexity, criticality, and the velocity/volume of change transformed AI/ML and automation from pilots into survival essentials. In response, enterprises increasingly turned to platforms for AI-enabled end-end visibility, workflows, and action.

It stands to reason that all of these changes would drive advances in how the core functions of IT service and IT operations work together. EMA undertook a deep dive research project with 400+ global IT leaders to understand the practical realities of IT ServiceOps today and in the near future.

Spoiler alert: Part technology and organizational approach, ServiceOps by any name will become the prevailing IT operational model because it is practical and makes good business sense.

Staffed by very different talent profiles aimed at distinct spheres of responsibility, the two groups traditionally interacted only when absolutely required by circumstances such as outages and changes required by DevOps. Today, the notion of ServiceOps represents the growing fact that in a healthy enterprise, it is increasingly difficult to say where one function ends and another begins. It's all about IT service to the business, and there is no service without effective IT operations.

Execution and service are inextricable.

It turns out that organizational siloes can be just as deadening as siloed toolsets and systems. The combination of AI and automation can mitigate both. Automation, AI/ML/analytics, and platforms that welcome cross-functional workflows make cooperation a practical reality. The research panel covered a lot of ground when asked.

How Do IT Operations and ITSM Collaborate Using AI/ML and Automation?

In this converged reality, both ITOps and ITSM take advantage of mutually beneficial solutions that are aimed at and measured by business goals. The long-heralded IT/business alignment is a natural byproduct of cross-functional capabilities, as well as a prerequisite to effective IT automation.

ITSM and ITOps remain distinct functions with specific charters. However, shared technology softens the boundaries and moves them closer organizationally. The research showed very strong correlation between the degree to which IT service and operations collaborate using AI-enabled automation and self-reported quality of IT service, end-user experience, business innovation, and increased IT budget.

ServiceOps, by whatever name, will soon be the prevailing IT operational model. It is the logical product of common sense and technology combined for practical purposes. Both IT service and IT operations have to be at the top of their respective games. Hitting that mark calls for platform-enabled, AI-assisted automation that flexibly connects people and machines across the enterprise.

Digital transformation, business innovation, and a world filled with surprises guarantee a constant state of change in IT. With a heavy assist from technology, the ServiceOps model positions IT to be organizationally as responsive and agile as the business demands.

Valerie O'Connell is EMA Research Director of Digital Service Execution

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Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

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ServiceOps: ITSM and ITOps Move from Cooperation to Collaboration

Valerie O'Connell
EMA

Nothing drives IT change like … change. There has been plenty of that to go around in the past few years. Planned digital transformation initiatives turbocharged into accelerated implementation as employees working from anywhere raised the stakes of day-to-day IT operations to business-critical levels.

Complexity, criticality, and the velocity/volume of change transformed AI/ML and automation from pilots into survival essentials. In response, enterprises increasingly turned to platforms for AI-enabled end-end visibility, workflows, and action.

It stands to reason that all of these changes would drive advances in how the core functions of IT service and IT operations work together. EMA undertook a deep dive research project with 400+ global IT leaders to understand the practical realities of IT ServiceOps today and in the near future.

Spoiler alert: Part technology and organizational approach, ServiceOps by any name will become the prevailing IT operational model because it is practical and makes good business sense.

Staffed by very different talent profiles aimed at distinct spheres of responsibility, the two groups traditionally interacted only when absolutely required by circumstances such as outages and changes required by DevOps. Today, the notion of ServiceOps represents the growing fact that in a healthy enterprise, it is increasingly difficult to say where one function ends and another begins. It's all about IT service to the business, and there is no service without effective IT operations.

Execution and service are inextricable.

It turns out that organizational siloes can be just as deadening as siloed toolsets and systems. The combination of AI and automation can mitigate both. Automation, AI/ML/analytics, and platforms that welcome cross-functional workflows make cooperation a practical reality. The research panel covered a lot of ground when asked.

How Do IT Operations and ITSM Collaborate Using AI/ML and Automation?

In this converged reality, both ITOps and ITSM take advantage of mutually beneficial solutions that are aimed at and measured by business goals. The long-heralded IT/business alignment is a natural byproduct of cross-functional capabilities, as well as a prerequisite to effective IT automation.

ITSM and ITOps remain distinct functions with specific charters. However, shared technology softens the boundaries and moves them closer organizationally. The research showed very strong correlation between the degree to which IT service and operations collaborate using AI-enabled automation and self-reported quality of IT service, end-user experience, business innovation, and increased IT budget.

ServiceOps, by whatever name, will soon be the prevailing IT operational model. It is the logical product of common sense and technology combined for practical purposes. Both IT service and IT operations have to be at the top of their respective games. Hitting that mark calls for platform-enabled, AI-assisted automation that flexibly connects people and machines across the enterprise.

Digital transformation, business innovation, and a world filled with surprises guarantee a constant state of change in IT. With a heavy assist from technology, the ServiceOps model positions IT to be organizationally as responsive and agile as the business demands.

Valerie O'Connell is EMA Research Director of Digital Service Execution

Hot Topics

The Latest

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...