Skip to main content

The State of IT Service Delivery: Next-Generation Technologies Force Change

Steve Francis

As IT service delivery solutions change, organizations are looking to next generation technologies (NGTs) to increase efficiency and deliver a better customer experience. Specific technologies like "cloud-to-the-edge" and artificial intelligence (AI), as well as marketplace shifts like the proliferation of the subscription economy and the importance of Digital Transformation (DX), necessitate action for organizations to keep pace with their competitors.

Only 20 percent of participants do not plan to modernize their IT service delivery solution

To examine the current state of IT service delivery – and anticipate where it leads next – LogicMonitor polled nearly 100 ServiceNow Knowledge18 attendees and LogicMonitor customers for the State of IT Service Delivery survey. The results are clear: IT service delivery is evolving, with 80 percent of the survey participants already implementing or planning to implement a modern IT solution, shortly. Only 20 percent of participants do not plan to modernize their IT service delivery solution.

What’s facilitating this shift? Early-movers indicate they’re driven by the need to increase efficiency (80 percent), improve decision-making (76 percent), and offer a better customer experience (76 percent).

We also found that organizations are approaching this new State of IT Service Delivery in a common fashion: Next-Generation Technologies and monitoring.

Next-Generation Technologies Force Change

NGTs are impacting a wide spectrum of industries. Respondents identified four key NGTs enhancing their IT service delivery capabilities:

■ 60% see cloud-to-the-edge improving efficiency by processing at the edge of the network

■ 60% anticipate the effect the expansion of subscription economy will have on IT service

■ 57% believe that AI will deliver a better customer experience by automating routine error responses and improving time to resolution

■ 56% see digital transformation (DX) having a major effect on the IT process holistically. DX will reimagine the IT process and improve important customer touchpoints

As organizations anticipate the effect these NGTs will have, it’s crucial for them to track their system’s performance. 76 percent of survey participants believe an improved customer experience is a key reason they’re investing in IT service delivery, which can be threatened by system errors and outages caused by a botched NGT integration. As a result, businesses must focus on system monitoring.

Monitoring is Vital

Effective monitoring leads to increased efficiency, improved decision-making, and a better customer experience

84 percent of survey participants recognize the value that properly monitoring devices, apps, and services can have for a successful IT service delivery solution. Effective monitoring leads to increased efficiency, improved decision-making, and a better customer experience – the key reasons organizations are investing in IT service delivery in the first place.

Clearly monitoring is important, but what does good monitoring entail? Participants outlined the primary types of monitoring vital to IT service delivery: infrastructure performance monitoring, app performance monitoring, and log management.

Further, respondents described two key features of a monitoring solution: 82 percent list context-rich alerts designed to create a straightforward response process as crucial, and 77 percent want automated synchronization between the CMDB and the monitoring platform.

Approaching the New State of IT Service Delivery

NGTs are transforming how IT Service Delivery processes work. To keep pace with competitors in the evolving marketplace, companies should embrace these technologies and invest in effective monitoring processes to ensure the best customer experience possible.

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 ...

The State of IT Service Delivery: Next-Generation Technologies Force Change

Steve Francis

As IT service delivery solutions change, organizations are looking to next generation technologies (NGTs) to increase efficiency and deliver a better customer experience. Specific technologies like "cloud-to-the-edge" and artificial intelligence (AI), as well as marketplace shifts like the proliferation of the subscription economy and the importance of Digital Transformation (DX), necessitate action for organizations to keep pace with their competitors.

Only 20 percent of participants do not plan to modernize their IT service delivery solution

To examine the current state of IT service delivery – and anticipate where it leads next – LogicMonitor polled nearly 100 ServiceNow Knowledge18 attendees and LogicMonitor customers for the State of IT Service Delivery survey. The results are clear: IT service delivery is evolving, with 80 percent of the survey participants already implementing or planning to implement a modern IT solution, shortly. Only 20 percent of participants do not plan to modernize their IT service delivery solution.

What’s facilitating this shift? Early-movers indicate they’re driven by the need to increase efficiency (80 percent), improve decision-making (76 percent), and offer a better customer experience (76 percent).

We also found that organizations are approaching this new State of IT Service Delivery in a common fashion: Next-Generation Technologies and monitoring.

Next-Generation Technologies Force Change

NGTs are impacting a wide spectrum of industries. Respondents identified four key NGTs enhancing their IT service delivery capabilities:

■ 60% see cloud-to-the-edge improving efficiency by processing at the edge of the network

■ 60% anticipate the effect the expansion of subscription economy will have on IT service

■ 57% believe that AI will deliver a better customer experience by automating routine error responses and improving time to resolution

■ 56% see digital transformation (DX) having a major effect on the IT process holistically. DX will reimagine the IT process and improve important customer touchpoints

As organizations anticipate the effect these NGTs will have, it’s crucial for them to track their system’s performance. 76 percent of survey participants believe an improved customer experience is a key reason they’re investing in IT service delivery, which can be threatened by system errors and outages caused by a botched NGT integration. As a result, businesses must focus on system monitoring.

Monitoring is Vital

Effective monitoring leads to increased efficiency, improved decision-making, and a better customer experience

84 percent of survey participants recognize the value that properly monitoring devices, apps, and services can have for a successful IT service delivery solution. Effective monitoring leads to increased efficiency, improved decision-making, and a better customer experience – the key reasons organizations are investing in IT service delivery in the first place.

Clearly monitoring is important, but what does good monitoring entail? Participants outlined the primary types of monitoring vital to IT service delivery: infrastructure performance monitoring, app performance monitoring, and log management.

Further, respondents described two key features of a monitoring solution: 82 percent list context-rich alerts designed to create a straightforward response process as crucial, and 77 percent want automated synchronization between the CMDB and the monitoring platform.

Approaching the New State of IT Service Delivery

NGTs are transforming how IT Service Delivery processes work. To keep pace with competitors in the evolving marketplace, companies should embrace these technologies and invest in effective monitoring processes to ensure the best customer experience possible.

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 ...