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IT Leaders Report High ROI on Cloud Despite Avoidable Deployment Costs

Grant Duxbury
Aptum

An Aptum survey of 400 senior IT decision-makers across the UK, US and Canada to gauge the impact of cloud adoption reflects a disparity between the expected and actual costs of implementation for organizations. The third installment of Aptum's four-part Cloud Impact Study, A Bright Forecast on Cloud, presents data showing the benefits organizations gain from cloud computing, as well as mistakes to avoid during migration.

As organizations migrate workloads to different cloud platforms, they often run into unexpected challenges due to a lack of proactive planning. Here are a few key findings from Part 3 of the Cloud Impact Study:

80% of respondents unlock greater business profitability through cloud services

Cloud computing yields quantifiable gains for organizations, primarily through increased scalability and application integration, the report states. Delivering services through the cloud can make organizations more agile — increasing revenue by accelerating new product deployment while shrinking time to market.

Organizations also see profits through greater efficiencies, with 78% of respondents attributing this increase to cloud adoption. Cloud computing payment structures eliminate the expense of unnecessary hardware, and cloud-based automation frees up time for staff.

80% of respondents believe cloud computing is essential for the financial security of their organization

Organizations operating on the cloud utilize expenditure models and scalable infrastructure on demand, so they only pay for what they need, when they need it. They aren't populating their balance sheets with financial liabilities, altogether eliminating that security risk.

57% of organizations encounter unexpected costs from cloud deployment

Moving to the cloud isn't as simple as moving data from one data center to another. It's no longer about discrete steps, but rather a journey. There are some common mistakes seen throughout this journey that lead to the unexpected costs organizations report, such as a lack of understanding around the need for hybrid models to accommodate data not suited to the cloud. Another is not leveraging a consumption-based model approach that breaks down applications and services as needed.

As IT environments become more complex, it becomes harder to keep abreast of cloud spending and total overrun. Without clear oversight, cloud sprawl is unavoidable. A lack of visibility and governance can contribute significantly to the challenges of excessive cloud spend.

35% of respondents also report wasting IT spend due to inefficient use of cloud platforms. With the average business spending over a third (36%) of its technology budget on cloud computing, intelligent planning and knowledge of best practices are critical to avoid unexpected costs and delays in implementation.

Rather than taking a "cloud-first" approach, companies should move forward with a strategy-first philosophy. Start migrations by thinking about how the cloud will impact operations and how to best integrate it with other technologies to leverage its power. If businesses take this approach, they should come out with a cloud roadmap that is aligned with their desired objectives.

Unlocking the True Value of the Cloud

Inappropriate workload migration due to poor planning and lack of visibility is prevalent, costly and can impede the entire deployment process. Applications in unsuitable environments can also lead to unplanned hybrid cloud implementations that create additional complexities around visibility and security.

For businesses to understand the true total cost of ownership and deliver maximum value from their cloud investments, it's essential to consider all components of cloud architectures. Businesses must ensure cloud cost management is a company-wide initiative, with compliance, finance and other key stakeholders aware of cloud distributions. They also need to ensure IT teams have access to the expertise and tools to control it effectively. Successful cloud migration requires buy in not just from IT or departments — but from senior leadership.

However, as the report reveals, most organizations need help unlocking the true value of the cloud. By working with a managed service provider with a strong heritage of traditional infrastructure management, cloud consulting and IT transformational expertise, organizations can build robust, high-performance hybrid cloud strategies that maximize business outcomes to drive business transformation and success.

Grant Duxbury is Global Director, Advisory & Consulting Services, at Aptum

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 ...

IT Leaders Report High ROI on Cloud Despite Avoidable Deployment Costs

Grant Duxbury
Aptum

An Aptum survey of 400 senior IT decision-makers across the UK, US and Canada to gauge the impact of cloud adoption reflects a disparity between the expected and actual costs of implementation for organizations. The third installment of Aptum's four-part Cloud Impact Study, A Bright Forecast on Cloud, presents data showing the benefits organizations gain from cloud computing, as well as mistakes to avoid during migration.

As organizations migrate workloads to different cloud platforms, they often run into unexpected challenges due to a lack of proactive planning. Here are a few key findings from Part 3 of the Cloud Impact Study:

80% of respondents unlock greater business profitability through cloud services

Cloud computing yields quantifiable gains for organizations, primarily through increased scalability and application integration, the report states. Delivering services through the cloud can make organizations more agile — increasing revenue by accelerating new product deployment while shrinking time to market.

Organizations also see profits through greater efficiencies, with 78% of respondents attributing this increase to cloud adoption. Cloud computing payment structures eliminate the expense of unnecessary hardware, and cloud-based automation frees up time for staff.

80% of respondents believe cloud computing is essential for the financial security of their organization

Organizations operating on the cloud utilize expenditure models and scalable infrastructure on demand, so they only pay for what they need, when they need it. They aren't populating their balance sheets with financial liabilities, altogether eliminating that security risk.

57% of organizations encounter unexpected costs from cloud deployment

Moving to the cloud isn't as simple as moving data from one data center to another. It's no longer about discrete steps, but rather a journey. There are some common mistakes seen throughout this journey that lead to the unexpected costs organizations report, such as a lack of understanding around the need for hybrid models to accommodate data not suited to the cloud. Another is not leveraging a consumption-based model approach that breaks down applications and services as needed.

As IT environments become more complex, it becomes harder to keep abreast of cloud spending and total overrun. Without clear oversight, cloud sprawl is unavoidable. A lack of visibility and governance can contribute significantly to the challenges of excessive cloud spend.

35% of respondents also report wasting IT spend due to inefficient use of cloud platforms. With the average business spending over a third (36%) of its technology budget on cloud computing, intelligent planning and knowledge of best practices are critical to avoid unexpected costs and delays in implementation.

Rather than taking a "cloud-first" approach, companies should move forward with a strategy-first philosophy. Start migrations by thinking about how the cloud will impact operations and how to best integrate it with other technologies to leverage its power. If businesses take this approach, they should come out with a cloud roadmap that is aligned with their desired objectives.

Unlocking the True Value of the Cloud

Inappropriate workload migration due to poor planning and lack of visibility is prevalent, costly and can impede the entire deployment process. Applications in unsuitable environments can also lead to unplanned hybrid cloud implementations that create additional complexities around visibility and security.

For businesses to understand the true total cost of ownership and deliver maximum value from their cloud investments, it's essential to consider all components of cloud architectures. Businesses must ensure cloud cost management is a company-wide initiative, with compliance, finance and other key stakeholders aware of cloud distributions. They also need to ensure IT teams have access to the expertise and tools to control it effectively. Successful cloud migration requires buy in not just from IT or departments — but from senior leadership.

However, as the report reveals, most organizations need help unlocking the true value of the cloud. By working with a managed service provider with a strong heritage of traditional infrastructure management, cloud consulting and IT transformational expertise, organizations can build robust, high-performance hybrid cloud strategies that maximize business outcomes to drive business transformation and success.

Grant Duxbury is Global Director, Advisory & Consulting Services, at Aptum

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 ...