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3 Years In, How Has Windows 10 Changed Enterprise IT?

Patricia Diaz-Hymes

This summer marked three years since Microsoft announced Windows 10, its first "Windows as a service" Operating System (OS) that, despite its maturity, is still at the center of many heated conversations in the End User Computing (EUC) community.


Windows 10 brought with it a new Software-as-a-Service-like approach to updates, moving Microsoft and the millions of environments that depend on it, more frequent, bundled updates. Whether you believe the shift was for better or worse, one thing is certain, this "as a service" model is a natural progression for today's operating systems, evidenced by OSX, Android and iOS, which have predated Microsoft's approach by years. That is why Windows 10 is changing not only how frequently updates are pushed out, but inherently how technology is purchased, how people consume it, and perhaps most importantly, how IT is run.

Let's take a look at how Windows 10 has impacted these three key areas over the past three years:

Both Gartner and IDC have seen a Growth in Hardware Sales

As with any refresh cycle, migrations to Windows 10 have impacted hardware sales. In fact, according to Peter Bright in a recent Ars Technica post, when it comes to Microsoft sales, "the general pattern over the last few quarters is that business sales have been robust even as consumer demand continues to soften."

While this increase may not come as a surprise to most of us in hindsight, refresh cycles can take IT teams by surprise when it comes to the necessary hardware update requirements. When Windows 10 was first introduced, many IT departments did not understand the graphical implications of the new OS, even for non-graphics-heavy users. In fact, in a Lakeside Software analysis of Windows 7 vs Windows 10, it was determined that, "Graphics usage increases 32% from Windows 7 (8.58%) to Windows 10 (11.30%)." And that is not due to any fault of IT's own – this under provisioning or miscalculation of compute resources is due in part to the lack of visibility IT teams have into the hardware (and other) requirements of business-driven refresh cycles.

Windows as a Service (WaaS) has Altered the Employee Experience

With its new servicing structure, Windows 10 has introduced Evergreen IT to the OS. A term first coined by PwC in 2009, Evergreen IT speaks to the benefits IT infrastructure can enjoy from adopting key attributes of cloud computing. In true evergreen fashion, Windows 10 is ever updating, with feature updates twice per year, rather than every 3-5 years previously, and bundled quality updates every month.

Just as the shift to evergreen operating systems has very real implications for IT, employees living and working in this new OS also experience a change and shift in the way they work. While more frequent feature and quality updates mean better patching and more optimized desktops, it may also mean compromised endpoint performance to which users often find workarounds, such as uninstalling updates. In light of this, Microsoft has given users the ability to schedule reboots and has even dabbled in using machine learning to improve user experience, particularly when it comes to reboots.

IT Operations Have and Will Continue to Adapt

Traditionally, IT has taken a reactive stance to supporting users and business-critical resources. Take for instance, the performance implications of the Meltdown and Spectre patches which, after being pushed out, showed noticeable CPU impact on endpoints. Most IT teams had no choice but to be reactive about improving end-user experience in this case.

And I am not suggesting that this reactive stance is due to any fault of IT's own. I argue that it is due to a lack of visibility into how updates and patches may shift the IT landscape. With Windows 10/Evergreen pushing out updates that may or may not impact endpoint performance, it is more critical than ever to understand what the impact of future updates may have on the environment so that, given the update, IT can act accordingly and minimize the impact on end users. This takes a shift in how IT operates — from gathering historical data to making sense of it — in order to predict and proactively act on that data

The Rising Importance of Workspace Analytics

With Microsoft's announcement on ending support for Windows 7 in January of 2020, it is clear that Windows 10 is showing strong growth despite the mix of anticipation and concerns around its servicing structure. And while it is true that Windows 7 is still the most popular version of Windows, projections indicate that the throne will soon be passed on to Windows 10.

Whether you are a part of the group that has migrated over or not, many of the hardships IT teams encounter with managing and working in a Windows 10 environment, including the three areas outlined above, can be lessened my gathering and making sense of endpoint data. This practice is called Workspace Analytics and it is an up-and-coming technology that can help answer the following:

- How ready is my environment for Windows 10 and what hardware/other changes are needed to make the migration successful?

- What is the end-user experience in my environment before, during and after an update? Why and how can I improve end-user experience?

- How can I be proactive about updates that may impact my end-users and how I run my environment?

Are you seeing other areas that are being affected by the migration? As we continue to see the growth of Windows 10 in enterprise IT, monitor the trends in how it is impacting your technology, users and how you run your environment so that you can keep evolving in lockstep with your IT stack.

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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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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 ...

3 Years In, How Has Windows 10 Changed Enterprise IT?

Patricia Diaz-Hymes

This summer marked three years since Microsoft announced Windows 10, its first "Windows as a service" Operating System (OS) that, despite its maturity, is still at the center of many heated conversations in the End User Computing (EUC) community.


Windows 10 brought with it a new Software-as-a-Service-like approach to updates, moving Microsoft and the millions of environments that depend on it, more frequent, bundled updates. Whether you believe the shift was for better or worse, one thing is certain, this "as a service" model is a natural progression for today's operating systems, evidenced by OSX, Android and iOS, which have predated Microsoft's approach by years. That is why Windows 10 is changing not only how frequently updates are pushed out, but inherently how technology is purchased, how people consume it, and perhaps most importantly, how IT is run.

Let's take a look at how Windows 10 has impacted these three key areas over the past three years:

Both Gartner and IDC have seen a Growth in Hardware Sales

As with any refresh cycle, migrations to Windows 10 have impacted hardware sales. In fact, according to Peter Bright in a recent Ars Technica post, when it comes to Microsoft sales, "the general pattern over the last few quarters is that business sales have been robust even as consumer demand continues to soften."

While this increase may not come as a surprise to most of us in hindsight, refresh cycles can take IT teams by surprise when it comes to the necessary hardware update requirements. When Windows 10 was first introduced, many IT departments did not understand the graphical implications of the new OS, even for non-graphics-heavy users. In fact, in a Lakeside Software analysis of Windows 7 vs Windows 10, it was determined that, "Graphics usage increases 32% from Windows 7 (8.58%) to Windows 10 (11.30%)." And that is not due to any fault of IT's own – this under provisioning or miscalculation of compute resources is due in part to the lack of visibility IT teams have into the hardware (and other) requirements of business-driven refresh cycles.

Windows as a Service (WaaS) has Altered the Employee Experience

With its new servicing structure, Windows 10 has introduced Evergreen IT to the OS. A term first coined by PwC in 2009, Evergreen IT speaks to the benefits IT infrastructure can enjoy from adopting key attributes of cloud computing. In true evergreen fashion, Windows 10 is ever updating, with feature updates twice per year, rather than every 3-5 years previously, and bundled quality updates every month.

Just as the shift to evergreen operating systems has very real implications for IT, employees living and working in this new OS also experience a change and shift in the way they work. While more frequent feature and quality updates mean better patching and more optimized desktops, it may also mean compromised endpoint performance to which users often find workarounds, such as uninstalling updates. In light of this, Microsoft has given users the ability to schedule reboots and has even dabbled in using machine learning to improve user experience, particularly when it comes to reboots.

IT Operations Have and Will Continue to Adapt

Traditionally, IT has taken a reactive stance to supporting users and business-critical resources. Take for instance, the performance implications of the Meltdown and Spectre patches which, after being pushed out, showed noticeable CPU impact on endpoints. Most IT teams had no choice but to be reactive about improving end-user experience in this case.

And I am not suggesting that this reactive stance is due to any fault of IT's own. I argue that it is due to a lack of visibility into how updates and patches may shift the IT landscape. With Windows 10/Evergreen pushing out updates that may or may not impact endpoint performance, it is more critical than ever to understand what the impact of future updates may have on the environment so that, given the update, IT can act accordingly and minimize the impact on end users. This takes a shift in how IT operates — from gathering historical data to making sense of it — in order to predict and proactively act on that data

The Rising Importance of Workspace Analytics

With Microsoft's announcement on ending support for Windows 7 in January of 2020, it is clear that Windows 10 is showing strong growth despite the mix of anticipation and concerns around its servicing structure. And while it is true that Windows 7 is still the most popular version of Windows, projections indicate that the throne will soon be passed on to Windows 10.

Whether you are a part of the group that has migrated over or not, many of the hardships IT teams encounter with managing and working in a Windows 10 environment, including the three areas outlined above, can be lessened my gathering and making sense of endpoint data. This practice is called Workspace Analytics and it is an up-and-coming technology that can help answer the following:

- How ready is my environment for Windows 10 and what hardware/other changes are needed to make the migration successful?

- What is the end-user experience in my environment before, during and after an update? Why and how can I improve end-user experience?

- How can I be proactive about updates that may impact my end-users and how I run my environment?

Are you seeing other areas that are being affected by the migration? As we continue to see the growth of Windows 10 in enterprise IT, monitor the trends in how it is impacting your technology, users and how you run your environment so that you can keep evolving in lockstep with your IT stack.

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 ...