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Unlocking the Keys to Meaningful Modernization

Rebecca Dilthey
Rocket Software

It's no secret that IT modernization has become one of the most critical ways for a business to stay competitive and ahead of the curve. But even while that notion is clear, the path toward achieving modernization is not. IT leaders today are bombarded with all kinds of trends and technologies that make the task of modernizing a complex, even risky endeavor. With so many options to choose from, where do IT leaders' priorities fall?

A recent survey conducted by Rocket Software of 275 U.-based IT directors and vice presidents in companies with more than 1,000 employees set out to answer exactly that.

What's Costing IT a Good Night's Sleep?

Whether it's a major push to reduce costs, drive results or overhaul the customer experience, the IT leaders in charge of modernization initiatives have all kinds of variables to consider. So, with all of those considerations weighing on IT leadership, what challenges have them losing sleep at night? Among those surveyed, 60% identified improving overall IT performance (60%), another 50% noted data security, 46% said process risk and compliance, and 41% highlighted the need to improve agility.

Of the majority who identified improving overall IT performance as a top concern, some of the biggest challenges facing their organizations ranged from IT infrastructure security to data security and even the present state of the economy.

So, we know the pain points for IT organizations, now it's time to look at what kind of action is being taken. And in spite of the many challenges, technologies, and complex factors involved with moving modernization forward, the survey found that IT leaders have a firm handle on where their priorities lie. Priorities that point back to one of the most influential strategies — hybrid cloud. Among the IT leaders surveyed, 65% said implementing a hybrid cloud strategy was a top priority. And, when asked, an overwhelming 93% of IT leaders agreed with the statement, "I believe my organization needs to embrace a hybrid infrastructure model that spans from mainframe to cloud."

Respondents also noted other priority areas that include data and content management (60%), DevOps (58%), infrastructure and application modernization (58%), automation (57%), and enterprise storage (35%).

Reducing Risk, Optimizing Resources, and Increasing Efficiency

With the emergence of new technologies and evolving approaches to IT, being able to define success is just as important as actually achieving it. IT leaders polled for the survey identified three main ways they measure, and define, success in their own organizations: Increased efficiency (71%), optimized resources (67%), and reduced risk (63%).

Mitigating Risk

Security is a major concern for every IT organization. And any approach to modernization needs to ensure that a business and its data and operations remain protected from attacks and breaches that could prove devastating. But even as risks loom large, many IT leaders feel they have a ways to go to be adequately prepared. In fact, only 33% of respondents said they were extremely confident that they have the right technology/software in place to execute an effective approach to IT risk management. Similarly, just 34% of respondents said they were extremely confident that they had the right processes in place to execute an effective approach to IT risk management.

When it comes to mitigating those risks, the most popular tools and processes IT leaders are turning to include data and systems access (63%), data availability (62%), process automation (47%), DevOps (46%), and orchestration and scheduling (33%). At a time where organizations are already under enormous pressure, IT leaders need to have the right tools and approach to security that instill confidence across processes, people, and technology.

Increasing Efficiency

No matter what position a business finds itself in, efficiency is critical for growth and long-term success. It's a reality that has only become more important in the wake of growing economic uncertainty. In fact, a majority (62%) of surveyed IT leaders reported focusing on efficiency as a result of economic instability.

As IT leadership make the push to become more efficient, there are a number of tools and processes that have gained favor in making that goal possible. Surveyed IT leaders ranked faster DevOps processes, automated processes, and increasing overall output as the top three measures that would be most impactful to increasing efficiency. Improving efficiency requires the right approach. And DevOps has seen its value rise as more organizations turn to it as a means for quickly improving the software development process.

Optimizing Resources

Between modernization initiatives and the demands of existing IT processes and workloads, IT leaders have their hands full as it is. As IT becomes more demanding, organizations are increasingly turning to automation to help lighten the load and streamline the most critical operations. But even with all the talk of automation, IT leaders still often find their teams spending valuable time dealing with manual tasks and managing and analyzing data. Of the IT leaders surveyed, 30% said they spend 6-10 hours per week on manual data entry and analysis, and 33% said they spend as much as 11-15 hours per week on these tasks.

Needing to dedicate that much time to tedious manual tasks isn't just inefficient, it also keeps IT staff away from other, more pressing responsibilities. When it comes to eliminating these manual processes, automation presents a powerful tool to help free up IT staff and ensure resources are being allocated effectively across the entire organization.

Modernization Coming Into Focus

IT leaders are faced with more decisions than ever before — hybrid cloud? Automation? DevOps? The sheer amount of choice can make charting a path forward feel overwhelming. But with the right tools, approach, and technologies IT teams can proceed with confidence and make a meaningful impact on any modernization effort.

Rebecca Dilthey is a Product Marketing Director at Rocket Software

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 ...

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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 ...

Unlocking the Keys to Meaningful Modernization

Rebecca Dilthey
Rocket Software

It's no secret that IT modernization has become one of the most critical ways for a business to stay competitive and ahead of the curve. But even while that notion is clear, the path toward achieving modernization is not. IT leaders today are bombarded with all kinds of trends and technologies that make the task of modernizing a complex, even risky endeavor. With so many options to choose from, where do IT leaders' priorities fall?

A recent survey conducted by Rocket Software of 275 U.-based IT directors and vice presidents in companies with more than 1,000 employees set out to answer exactly that.

What's Costing IT a Good Night's Sleep?

Whether it's a major push to reduce costs, drive results or overhaul the customer experience, the IT leaders in charge of modernization initiatives have all kinds of variables to consider. So, with all of those considerations weighing on IT leadership, what challenges have them losing sleep at night? Among those surveyed, 60% identified improving overall IT performance (60%), another 50% noted data security, 46% said process risk and compliance, and 41% highlighted the need to improve agility.

Of the majority who identified improving overall IT performance as a top concern, some of the biggest challenges facing their organizations ranged from IT infrastructure security to data security and even the present state of the economy.

So, we know the pain points for IT organizations, now it's time to look at what kind of action is being taken. And in spite of the many challenges, technologies, and complex factors involved with moving modernization forward, the survey found that IT leaders have a firm handle on where their priorities lie. Priorities that point back to one of the most influential strategies — hybrid cloud. Among the IT leaders surveyed, 65% said implementing a hybrid cloud strategy was a top priority. And, when asked, an overwhelming 93% of IT leaders agreed with the statement, "I believe my organization needs to embrace a hybrid infrastructure model that spans from mainframe to cloud."

Respondents also noted other priority areas that include data and content management (60%), DevOps (58%), infrastructure and application modernization (58%), automation (57%), and enterprise storage (35%).

Reducing Risk, Optimizing Resources, and Increasing Efficiency

With the emergence of new technologies and evolving approaches to IT, being able to define success is just as important as actually achieving it. IT leaders polled for the survey identified three main ways they measure, and define, success in their own organizations: Increased efficiency (71%), optimized resources (67%), and reduced risk (63%).

Mitigating Risk

Security is a major concern for every IT organization. And any approach to modernization needs to ensure that a business and its data and operations remain protected from attacks and breaches that could prove devastating. But even as risks loom large, many IT leaders feel they have a ways to go to be adequately prepared. In fact, only 33% of respondents said they were extremely confident that they have the right technology/software in place to execute an effective approach to IT risk management. Similarly, just 34% of respondents said they were extremely confident that they had the right processes in place to execute an effective approach to IT risk management.

When it comes to mitigating those risks, the most popular tools and processes IT leaders are turning to include data and systems access (63%), data availability (62%), process automation (47%), DevOps (46%), and orchestration and scheduling (33%). At a time where organizations are already under enormous pressure, IT leaders need to have the right tools and approach to security that instill confidence across processes, people, and technology.

Increasing Efficiency

No matter what position a business finds itself in, efficiency is critical for growth and long-term success. It's a reality that has only become more important in the wake of growing economic uncertainty. In fact, a majority (62%) of surveyed IT leaders reported focusing on efficiency as a result of economic instability.

As IT leadership make the push to become more efficient, there are a number of tools and processes that have gained favor in making that goal possible. Surveyed IT leaders ranked faster DevOps processes, automated processes, and increasing overall output as the top three measures that would be most impactful to increasing efficiency. Improving efficiency requires the right approach. And DevOps has seen its value rise as more organizations turn to it as a means for quickly improving the software development process.

Optimizing Resources

Between modernization initiatives and the demands of existing IT processes and workloads, IT leaders have their hands full as it is. As IT becomes more demanding, organizations are increasingly turning to automation to help lighten the load and streamline the most critical operations. But even with all the talk of automation, IT leaders still often find their teams spending valuable time dealing with manual tasks and managing and analyzing data. Of the IT leaders surveyed, 30% said they spend 6-10 hours per week on manual data entry and analysis, and 33% said they spend as much as 11-15 hours per week on these tasks.

Needing to dedicate that much time to tedious manual tasks isn't just inefficient, it also keeps IT staff away from other, more pressing responsibilities. When it comes to eliminating these manual processes, automation presents a powerful tool to help free up IT staff and ensure resources are being allocated effectively across the entire organization.

Modernization Coming Into Focus

IT leaders are faced with more decisions than ever before — hybrid cloud? Automation? DevOps? The sheer amount of choice can make charting a path forward feel overwhelming. But with the right tools, approach, and technologies IT teams can proceed with confidence and make a meaningful impact on any modernization effort.

Rebecca Dilthey is a Product Marketing Director at Rocket Software

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 ...