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Top ITSM Objectives: End User Experience and Aligning IT with the Business

Pete Goldin
APMdigest

Improving the end user experience and connecting IT to wider business objectives is a significant focal point for IT professionals, according to new survey conducted by Ivanti at this years' Service Desk & IT Support Show (SITS) in London.

72 percent of respondents cited "improving the end user experience" as one of their top three strategic management priorities.

When asked about which automation and analytic capabilities were most important for their organizations' ITSM initiatives this year, "advanced levels of workflow automation", "analytics for incident/problem and availability management" and "analytics for user experience and visibility into end-user problems" were IT professionals' top priorities.

The majority of respondents therefore seem to be applying ITSM to address self-service requirements.

Another vital concern is the need to free up the IT Department to drive business efficiency, thereby ensuring that the impact of ITSM enables wider business objectives to be achieved. For example, the research shows that 52 percent of respondents see ITSM reporting capabilities that place data in the hands of key decision makers as a core priority within their ITSM strategy.

However, only 50 percent of those surveyed saw ITSM as a tool to support crucial security and compliance processes. Of particular note, only 36 percent of those surveyed who work in the healthcare industry (this includes healthcare consultancies, suppliers and practitioners) identified security and compliance as a point of focus for ITSM. This is surprising given the upcoming GDPR legislation and the amount of personal, and highly sensitive, data that healthcare organisations hold on to internally. It is also concerning given the growing severity of external threats such as the recent global WannaCry and NotPetya ransomware attacks.

"Traditional hierarchies with manual IT processes and tools, plus complex user interfaces that do not give users what they want, struggle to be drivers of digital transformation. When we developed and put this survey out to the ITSM Professionals at SITS, the question on our mind was, what are UK IT Departments doing to break the status quo and become an enabler, rather than a barrier to business growth and productivity?" commented Ian Aitchison, Senior Product Director at Ivanti.

"Businesses require IT to help provide technology and solutions which drive the business forward, and not just support it" he added. "Through simplification, integration and automation, many tasks like onboarding new employees, and replacing lost or damaged phones, that used to consume time and money can now be automated. The process of automation allows IT to focus on innovation by changing the way we test, measure and create new services and revenue streams."

Pete Goldin is Editor and Publisher of APMdigest

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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 ...

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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 ...

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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.

Top ITSM Objectives: End User Experience and Aligning IT with the Business

Pete Goldin
APMdigest

Improving the end user experience and connecting IT to wider business objectives is a significant focal point for IT professionals, according to new survey conducted by Ivanti at this years' Service Desk & IT Support Show (SITS) in London.

72 percent of respondents cited "improving the end user experience" as one of their top three strategic management priorities.

When asked about which automation and analytic capabilities were most important for their organizations' ITSM initiatives this year, "advanced levels of workflow automation", "analytics for incident/problem and availability management" and "analytics for user experience and visibility into end-user problems" were IT professionals' top priorities.

The majority of respondents therefore seem to be applying ITSM to address self-service requirements.

Another vital concern is the need to free up the IT Department to drive business efficiency, thereby ensuring that the impact of ITSM enables wider business objectives to be achieved. For example, the research shows that 52 percent of respondents see ITSM reporting capabilities that place data in the hands of key decision makers as a core priority within their ITSM strategy.

However, only 50 percent of those surveyed saw ITSM as a tool to support crucial security and compliance processes. Of particular note, only 36 percent of those surveyed who work in the healthcare industry (this includes healthcare consultancies, suppliers and practitioners) identified security and compliance as a point of focus for ITSM. This is surprising given the upcoming GDPR legislation and the amount of personal, and highly sensitive, data that healthcare organisations hold on to internally. It is also concerning given the growing severity of external threats such as the recent global WannaCry and NotPetya ransomware attacks.

"Traditional hierarchies with manual IT processes and tools, plus complex user interfaces that do not give users what they want, struggle to be drivers of digital transformation. When we developed and put this survey out to the ITSM Professionals at SITS, the question on our mind was, what are UK IT Departments doing to break the status quo and become an enabler, rather than a barrier to business growth and productivity?" commented Ian Aitchison, Senior Product Director at Ivanti.

"Businesses require IT to help provide technology and solutions which drive the business forward, and not just support it" he added. "Through simplification, integration and automation, many tasks like onboarding new employees, and replacing lost or damaged phones, that used to consume time and money can now be automated. The process of automation allows IT to focus on innovation by changing the way we test, measure and create new services and revenue streams."

Pete Goldin is Editor and Publisher of APMdigest

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.