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CIOs Target Legacy IT in Push for Digital Transformation

CIOs around the globe are more determined than ever to achieve digital transformation within their organizations despite setbacks experienced over the past year, according to a survey by Logicalis.

The survey, which polled 890 CIOs across 23 countries, unearthed surprising findings this year. Although CIOs are determined to achieve digital transformation, optimism about their strides toward success has waned over the last 12 months.

While only 11 percent report their organizations have “no desire” for transformation, those that ideologically embrace digital transformation have made only minimal advancements to date:

■ Just 5 percent classify their organizations as “digital innovators,” down from 6 percent in last year’s survey.

■ Fewer CIOs (19 percent) see their organizations as early adopters today, a step back from last year’s 22 percent.

■ However, the proportion of CIOs that characterize themselves as part of an early majority with digital transformation rose from 45 percent last year to 49 percent this year, illustrating that, despite difficulties, IT leaders are moving ahead with digital transformation plans.

Overcoming Difficulties

The main barriers to delivering digital transformation, CIOs say, include complexity, cost, culture, skills and security issues. Notably, 44 percent of CIOs cite the complexity of legacy technology as their top obstacle, while 50 percent point to cost, 56 percent name organizational culture as their largest issue, 34 percent say it’s a lack of skills, and 32 percent identify security as their biggest hurdle.

Far from discouraged, CIOs around the world have big plans for overcoming these digital transformation barriers:

■ 51 percent say they plan to replace and/or adapt existing infrastructure.

■ 51 percent plan to attempt culture change within their organizations.

■ 38 percent will address skills shortages through increased training and development.

■ 31 percent expect to invest in extra security capabilities.

“The way businesses view technology is undergoing an exciting yet fundamental shift,” says Vince DeLuca, CEO of Logicalis US. “The goal behind technology is no longer simply about implementing and managing tools that enable people to do their jobs. In a digitally transformed enterprise, it’s about giving people access to the information they need to fuel business agility and growth and to empower collaboration that will create business models no one has yet imagined. Digital transformation is the foundation upon which this new way of doing business will be built, and as this year’s Global CIO Survey indicates, IT leaders around the world not only recognize this, but they are determined to provide the platform their organizations need to embrace the change that is to come.”

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 ...

CIOs Target Legacy IT in Push for Digital Transformation

CIOs around the globe are more determined than ever to achieve digital transformation within their organizations despite setbacks experienced over the past year, according to a survey by Logicalis.

The survey, which polled 890 CIOs across 23 countries, unearthed surprising findings this year. Although CIOs are determined to achieve digital transformation, optimism about their strides toward success has waned over the last 12 months.

While only 11 percent report their organizations have “no desire” for transformation, those that ideologically embrace digital transformation have made only minimal advancements to date:

■ Just 5 percent classify their organizations as “digital innovators,” down from 6 percent in last year’s survey.

■ Fewer CIOs (19 percent) see their organizations as early adopters today, a step back from last year’s 22 percent.

■ However, the proportion of CIOs that characterize themselves as part of an early majority with digital transformation rose from 45 percent last year to 49 percent this year, illustrating that, despite difficulties, IT leaders are moving ahead with digital transformation plans.

Overcoming Difficulties

The main barriers to delivering digital transformation, CIOs say, include complexity, cost, culture, skills and security issues. Notably, 44 percent of CIOs cite the complexity of legacy technology as their top obstacle, while 50 percent point to cost, 56 percent name organizational culture as their largest issue, 34 percent say it’s a lack of skills, and 32 percent identify security as their biggest hurdle.

Far from discouraged, CIOs around the world have big plans for overcoming these digital transformation barriers:

■ 51 percent say they plan to replace and/or adapt existing infrastructure.

■ 51 percent plan to attempt culture change within their organizations.

■ 38 percent will address skills shortages through increased training and development.

■ 31 percent expect to invest in extra security capabilities.

“The way businesses view technology is undergoing an exciting yet fundamental shift,” says Vince DeLuca, CEO of Logicalis US. “The goal behind technology is no longer simply about implementing and managing tools that enable people to do their jobs. In a digitally transformed enterprise, it’s about giving people access to the information they need to fuel business agility and growth and to empower collaboration that will create business models no one has yet imagined. Digital transformation is the foundation upon which this new way of doing business will be built, and as this year’s Global CIO Survey indicates, IT leaders around the world not only recognize this, but they are determined to provide the platform their organizations need to embrace the change that is to come.”

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 ...