Top CIO Challenges: IT Complexity and Managing IT Performance

Learn more about Dynatrace

Digital transformation, migration to the enterprise cloud and increasing customer demands are creating a surge in IT complexity and the associated costs of managing it. Technical leaders around the world are concerned about the effect this has on IT performance and ultimately, their business according to a new report from Dynatrace, based on an independent global survey of 800 CIOs, Top Challenges for CIOs in a Software-Driven, Hybrid, Multi-Cloud World.

CIO responses to the survey indicate that lost revenue (49%) and reputational damage (52%) are among the biggest concerns as businesses transform into software businesses and move to the cloud.

And, as CIOs struggle to prevent these concerns from becoming reality, IT teams now spend 33% of their time dealing with digital performance problems, costing businesses an average of $3.3 million annually, compared to $2.5 million in 2018; an increase of 34%. To combat this, 88% of CIOs say AI will be critical to IT’s ability to master increasing complexity.

Software is Transforming Every Business

Every company, in every industry, is transforming into a software business. The way enterprises interact with customers, assure quality experiences and optimize revenues is driven by applications and the hybrid, multi-cloud environments underpinning them. Success or failure comes down to the software supporting these efforts. The pressure of this "run-the-business" software performing properly has significant ramifications for IT professionals.

According to the survey:

■ 44% of CIOs fear there could be a threat to the existence of their business if they are unable to manage IT performance.

■ As complexity continues to grow, 74% of CIOs say it could soon become extremely difficult to manage performance efficiently.


Enterprise "Cloud-First" Strategies Increase Complexity

Underpinning this software revolution is the enterprise cloud, allowing companies to innovate faster and better meet the needs of customers. The enterprise cloud is dynamic, hybrid, multi-cloud, and web-scale, containing hundreds of technologies, millions of lines of code and billions of dependencies. However, this transformation isn’t simply about lifting and shifting apps to the cloud, it’s a fundamental shift in how applications are built, deployed and operated.

According to the survey:

■ The majority of CIOs are already using or are planning to deploy microservices (88%), containers (86%), serverless computing (85%), PaaS (89%), SaaS (94%), IaaS (91%) and private cloud (95%) in the next 12 months.

■ The average mobile or web application transaction crosses 37 different technology systems or components. This brings an inherent increase in IT complexity, making it harder for organizations to manage performance.

The Age of the Customer Increases Pressure to Deliver Great Experiences

We are squarely in the age of the customer, where high quality service is paramount due to the ease with which customers will try competitive offerings and share their experiences instantly via social media.

The research highlights the extent to which businesses are struggling to combat IT complexity that threatens the customer experience, with CIOs revealing: on average, organizations have suffered 6 IT outages where user-experiences, business revenues or operations were impacted in the last 12 months.

IT Teams Are Feeling the Strain

Digital transformation, migration to the enterprise cloud and increasing customer demands are collectively putting pressure on IT teams, who continue to feel the strain, especially as it relates to performance. Revealing the extent of this dilemma, key findings of the research also show that:

■ More than three quarters of CIOs (76%) say they don’t have complete visibility into application performance in cloud-native architectures.

■ 78% of CIOs are frustrated that so much time is spent setting up monitoring for different cloud environments when deploying new services.

■ IT teams now spend around 33% of their time tackling performance problems.


Exploring the potential antidote to these challenges, the research further reveals that 88% of CIOs say that they believe AI will be critical to IT’s ability to master increasing complexity.

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Top CIO Challenges: IT Complexity and Managing IT Performance

Learn more about Dynatrace

Digital transformation, migration to the enterprise cloud and increasing customer demands are creating a surge in IT complexity and the associated costs of managing it. Technical leaders around the world are concerned about the effect this has on IT performance and ultimately, their business according to a new report from Dynatrace, based on an independent global survey of 800 CIOs, Top Challenges for CIOs in a Software-Driven, Hybrid, Multi-Cloud World.

CIO responses to the survey indicate that lost revenue (49%) and reputational damage (52%) are among the biggest concerns as businesses transform into software businesses and move to the cloud.

And, as CIOs struggle to prevent these concerns from becoming reality, IT teams now spend 33% of their time dealing with digital performance problems, costing businesses an average of $3.3 million annually, compared to $2.5 million in 2018; an increase of 34%. To combat this, 88% of CIOs say AI will be critical to IT’s ability to master increasing complexity.

Software is Transforming Every Business

Every company, in every industry, is transforming into a software business. The way enterprises interact with customers, assure quality experiences and optimize revenues is driven by applications and the hybrid, multi-cloud environments underpinning them. Success or failure comes down to the software supporting these efforts. The pressure of this "run-the-business" software performing properly has significant ramifications for IT professionals.

According to the survey:

■ 44% of CIOs fear there could be a threat to the existence of their business if they are unable to manage IT performance.

■ As complexity continues to grow, 74% of CIOs say it could soon become extremely difficult to manage performance efficiently.


Enterprise "Cloud-First" Strategies Increase Complexity

Underpinning this software revolution is the enterprise cloud, allowing companies to innovate faster and better meet the needs of customers. The enterprise cloud is dynamic, hybrid, multi-cloud, and web-scale, containing hundreds of technologies, millions of lines of code and billions of dependencies. However, this transformation isn’t simply about lifting and shifting apps to the cloud, it’s a fundamental shift in how applications are built, deployed and operated.

According to the survey:

■ The majority of CIOs are already using or are planning to deploy microservices (88%), containers (86%), serverless computing (85%), PaaS (89%), SaaS (94%), IaaS (91%) and private cloud (95%) in the next 12 months.

■ The average mobile or web application transaction crosses 37 different technology systems or components. This brings an inherent increase in IT complexity, making it harder for organizations to manage performance.

The Age of the Customer Increases Pressure to Deliver Great Experiences

We are squarely in the age of the customer, where high quality service is paramount due to the ease with which customers will try competitive offerings and share their experiences instantly via social media.

The research highlights the extent to which businesses are struggling to combat IT complexity that threatens the customer experience, with CIOs revealing: on average, organizations have suffered 6 IT outages where user-experiences, business revenues or operations were impacted in the last 12 months.

IT Teams Are Feeling the Strain

Digital transformation, migration to the enterprise cloud and increasing customer demands are collectively putting pressure on IT teams, who continue to feel the strain, especially as it relates to performance. Revealing the extent of this dilemma, key findings of the research also show that:

■ More than three quarters of CIOs (76%) say they don’t have complete visibility into application performance in cloud-native architectures.

■ 78% of CIOs are frustrated that so much time is spent setting up monitoring for different cloud environments when deploying new services.

■ IT teams now spend around 33% of their time tackling performance problems.


Exploring the potential antidote to these challenges, the research further reveals that 88% of CIOs say that they believe AI will be critical to IT’s ability to master increasing complexity.

Related Links

Hot Topics

The Latest

The Performance Bottleneck in Enterprise AI Has Been Exposed – Now We Must Fix It

Performance bottlenecks aren't uncommon when it comes to rolling out new technology, regardless of how capable or game-changing that technology might be. Every generation of new tech has encountered roadblocks that had to be overcome before it was truly able to shine. Virtualization forced organizations to rethink resource allocation, cloud transformation had us shift our focus toward scalability and elasticity, and microservices introduced entirely new challenges around observability and distributed systems. There's something different about AI, however ...

What Capital Markets Can Teach Enterprises About Integrated Data Infrastructure

Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

Why AI in IT Is Producing High Productivity but Heavy Workloads

AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

Implementing AI Isn't the Hard Part Anymore - Adoption Is

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

The Incident Load Is Rising, but Recovery Times Aren't Moving

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

Your AI Pipeline May Have a Document Observability Problem

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

The SIEM Isn't the Problem. Your Telemetry Architecture Is

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

As AI Scales Across Enterprises, Breaking Points Emerge

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

Preparing Network Infrastructure for AI Starts with the Basics

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Agentic Operations Begin with Governed Middleware Access

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...