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The Changing Game of IT Service Management

Dennis Drogseth

If you think that ITSM (IT Service Management) is static and old hat, think twice. A huge number of innovations are just emerging. Some have been a long time in coming; while others are unexpected surprises — as analytics and automation are changing the ITSM game dramatically.

Here are some trends that I’ve seen in 2014 that I expect will grow in importance in 2015. Some may explode into prominence, but I expect most will continue to rise more gradually into industry consciousness, which is typical of the more profound transformations versus those that enjoy a chic but shallow industry cachet.

■ As the role of IT is changing to become a more front-office (as opposed to back-office) presence, ITSM will become a yet more critical part of that transformation. Why is this? ITSM can become a new center for IT insights, governance, automation, and analytics to come together with a fully human voice, capturing vital perspectives on real user experience and sharing them with development and operations. But to do so, ITSM will have to change in its technology adoption priorities, as indicated in the following discussions.

■ Mobile, wireless, and social IT will become a more important part of that transformation — as end-point awareness becomes ever more critical in delivering, sustaining and optimizing IT services. Critical “areas to watch” in 2015 include: managing and optimizing endpoints as performing assets while cultivating the powers of enhanced GUI designs, mobile and social IT to promote improved service interaction.

■ Automation will be one of the biggest game changers for ITSM, with the potential to impact virtually every other “game-changer” here. While ITSM is traditionally viewed in terms of “service desk”, as it evolves it will reach out through automation and analytics to include operations, and even development, far more proactively. This is true whether we’re talking about configuration automation, more advanced workflows, runbook or IT process automation, or other automation investments.

■ Perhaps nowhere will automation become more conspicuous than in the changing role of change management (including release and configuration management) from slow, laborious and fragmented manual processes to more streamlined and yet more service-aware capabilities. In 2015, I predict that automation, service modeling, and analytics will begin to come together in new ways, with far less overhead than in the past — transforming not only ITSM but service management even more broadly. This will be one area in 2015 where agile, DevOps, and ITSM will begin to converge.

■ None of the above will work, however, without attention to governance, process, dialog, and business alignment. Fragmented, piecemeal automation can result in train wrecks, while cloud computing is adding ever more options that need to be assessed for performance, usage, capacity, and costs. ITSM will begin to play a role as an interactive center for that dialog in 2015, at least in some IT environments, with a new face and a new look.

Does all this sound like wishful thinking? Maybe, but I’ve already seen good evidence supporting everything here.

I’m also holding myself accountable, as we’ll be doing some unique research beginning in January — looking at the future of ITSM. If the data proves me right, or even if it proves me wrong, I promise you’ll hear from me when the results are in some time in February.

Hot Topics

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The Changing Game of IT Service Management

Dennis Drogseth

If you think that ITSM (IT Service Management) is static and old hat, think twice. A huge number of innovations are just emerging. Some have been a long time in coming; while others are unexpected surprises — as analytics and automation are changing the ITSM game dramatically.

Here are some trends that I’ve seen in 2014 that I expect will grow in importance in 2015. Some may explode into prominence, but I expect most will continue to rise more gradually into industry consciousness, which is typical of the more profound transformations versus those that enjoy a chic but shallow industry cachet.

■ As the role of IT is changing to become a more front-office (as opposed to back-office) presence, ITSM will become a yet more critical part of that transformation. Why is this? ITSM can become a new center for IT insights, governance, automation, and analytics to come together with a fully human voice, capturing vital perspectives on real user experience and sharing them with development and operations. But to do so, ITSM will have to change in its technology adoption priorities, as indicated in the following discussions.

■ Mobile, wireless, and social IT will become a more important part of that transformation — as end-point awareness becomes ever more critical in delivering, sustaining and optimizing IT services. Critical “areas to watch” in 2015 include: managing and optimizing endpoints as performing assets while cultivating the powers of enhanced GUI designs, mobile and social IT to promote improved service interaction.

■ Automation will be one of the biggest game changers for ITSM, with the potential to impact virtually every other “game-changer” here. While ITSM is traditionally viewed in terms of “service desk”, as it evolves it will reach out through automation and analytics to include operations, and even development, far more proactively. This is true whether we’re talking about configuration automation, more advanced workflows, runbook or IT process automation, or other automation investments.

■ Perhaps nowhere will automation become more conspicuous than in the changing role of change management (including release and configuration management) from slow, laborious and fragmented manual processes to more streamlined and yet more service-aware capabilities. In 2015, I predict that automation, service modeling, and analytics will begin to come together in new ways, with far less overhead than in the past — transforming not only ITSM but service management even more broadly. This will be one area in 2015 where agile, DevOps, and ITSM will begin to converge.

■ None of the above will work, however, without attention to governance, process, dialog, and business alignment. Fragmented, piecemeal automation can result in train wrecks, while cloud computing is adding ever more options that need to be assessed for performance, usage, capacity, and costs. ITSM will begin to play a role as an interactive center for that dialog in 2015, at least in some IT environments, with a new face and a new look.

Does all this sound like wishful thinking? Maybe, but I’ve already seen good evidence supporting everything here.

I’m also holding myself accountable, as we’ll be doing some unique research beginning in January — looking at the future of ITSM. If the data proves me right, or even if it proves me wrong, I promise you’ll hear from me when the results are in some time in February.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...