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Digital Transformation Projects Show Increasing Improvements

Despite the challenges of the last two years, enterprises have made significant progress with digital transformation — 79% of enterprises have made significant, transformative or even revolutionary improvements to the end user experience through digital transformation over the past year, compared to 73% in 2019 and 72% in 2020, according to Digital Transformation — Lessons Learned and Strategic Setbacks, a global survey of 650 IT leaders conducted by Couchbase.

And the outlook is optimistic — on average, enterprises plan to increase their investment in digital transformation by 46% over the next 12 months.

However, enterprises still need to be aware of digital transformation challenges — 81% of enterprises had digital transformation projects fail, suffer delays or be scaled back in the past year, at an average cost of $4.12 million.

A further 82% were prevented from pursuing digital transformation projects that they wanted to implement due to factors such as a lack of resources or funds (reported by 26%), a lack of skills to deliver the project (24%) or the complexity of implementing technologies (23%).

The consequences of these failed or missed projects can be more than wasted funds — 55% of enterprises that suffered issues with their digital transformation projects had to delay their strategic goals by three months or more, or reset them completely.

Other potential consequences of failing to keep pace identified by respondents include losing valuable staff to more innovative competitors — whether in IT (41%) or other areas of the business (40%); struggling to secure finance or undergo a successful IPO (31%); or going out of business or being absorbed by a competitor (26%).

"The progress in organizations' digital transformation ambitions over the past 12 months is clear, and there's a bright future ahead," said Ravi Mayuram, cto at Couchbase. "Ideally we'll now begin to see enterprises putting into practice projects and ideas that weren't previously considered possible. For this to become reality, organizations need to learn the lessons of the last two years and address the challenges they face, or a large proportion of that 46% increase in investment may be wasted, too. IT teams need support from across the business, together with the resources they need, and the right skills and technology to succeed. From embracing the cloud, to making the best use of data, enterprises that can make use of new technologies will be best placed to thrive."

Lessons Learned

The past two years have had a transformative impact on IT teams.

95% of respondents have implemented or investigated digital transformation opportunities that would not have been realistic at the end of 2019 — from hybrid working (nearly 47%) to moving to the cloud (46%), replacing legacy technology and processes (42%), changing the way the business operates (36%) and creating new business offerings (35%).

Other findings included:
 
■ 99% of enterprises say they learned lessons from the pandemic: including the importance of supporting remote and hybrid working (45%); the need for continuous investment and research in digital transformation technologies (41%); and how to better engage the wider business in digital transformation strategy (34%).

■ Investment priorities are shifting compared to 2019: While security is still the top priority for enterprises, and hybrid working received an understandable boost, modernizing existing technology has fallen as a priority, while adopting new technologies has grown — suggesting enterprises recognize they need completely new, modern tools in order to face the future.

■ Ways of working have changed: 88% of respondents say their digital transformation goals have fundamentally changed over the last two years; 95% have accelerated their application modernization strategies; 90% have changed the way they budget for digital transformation; and 93% say digital transformation projects over the last two years represent permanent changes to the way their business's way of operating or working.

■ End users are the focus: 88% of respondents said their digital transformation projects had been driven more by changes in user behavior than by creating new business opportunities.

Digital transformation ... needs to be the responsibility of, and driven by, the whole C-suite, rather than left solely in IT's hands

"This is an exciting time for the IT industry. We are entering a period of extreme creativity, as organizations shift from digital transformation driven by reacting to outside events, such as the pandemic or competitors' progress, to a more proactive approach driven by ideas from within the business," continued Mayuram. "For this new creativity to work, it needs to be driven from the top. Digital transformation shouldn't only be aligned to strategic goals. As a transformative business asset it needs to be the responsibility of, and driven by, the whole C-suite, rather than left solely in IT's hands. If businesses can do this and put the lessons they learned from the last two years into practice, then the future looks very bright indeed."

The Latest

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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? ...

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 ...

Digital Transformation Projects Show Increasing Improvements

Despite the challenges of the last two years, enterprises have made significant progress with digital transformation — 79% of enterprises have made significant, transformative or even revolutionary improvements to the end user experience through digital transformation over the past year, compared to 73% in 2019 and 72% in 2020, according to Digital Transformation — Lessons Learned and Strategic Setbacks, a global survey of 650 IT leaders conducted by Couchbase.

And the outlook is optimistic — on average, enterprises plan to increase their investment in digital transformation by 46% over the next 12 months.

However, enterprises still need to be aware of digital transformation challenges — 81% of enterprises had digital transformation projects fail, suffer delays or be scaled back in the past year, at an average cost of $4.12 million.

A further 82% were prevented from pursuing digital transformation projects that they wanted to implement due to factors such as a lack of resources or funds (reported by 26%), a lack of skills to deliver the project (24%) or the complexity of implementing technologies (23%).

The consequences of these failed or missed projects can be more than wasted funds — 55% of enterprises that suffered issues with their digital transformation projects had to delay their strategic goals by three months or more, or reset them completely.

Other potential consequences of failing to keep pace identified by respondents include losing valuable staff to more innovative competitors — whether in IT (41%) or other areas of the business (40%); struggling to secure finance or undergo a successful IPO (31%); or going out of business or being absorbed by a competitor (26%).

"The progress in organizations' digital transformation ambitions over the past 12 months is clear, and there's a bright future ahead," said Ravi Mayuram, cto at Couchbase. "Ideally we'll now begin to see enterprises putting into practice projects and ideas that weren't previously considered possible. For this to become reality, organizations need to learn the lessons of the last two years and address the challenges they face, or a large proportion of that 46% increase in investment may be wasted, too. IT teams need support from across the business, together with the resources they need, and the right skills and technology to succeed. From embracing the cloud, to making the best use of data, enterprises that can make use of new technologies will be best placed to thrive."

Lessons Learned

The past two years have had a transformative impact on IT teams.

95% of respondents have implemented or investigated digital transformation opportunities that would not have been realistic at the end of 2019 — from hybrid working (nearly 47%) to moving to the cloud (46%), replacing legacy technology and processes (42%), changing the way the business operates (36%) and creating new business offerings (35%).

Other findings included:
 
■ 99% of enterprises say they learned lessons from the pandemic: including the importance of supporting remote and hybrid working (45%); the need for continuous investment and research in digital transformation technologies (41%); and how to better engage the wider business in digital transformation strategy (34%).

■ Investment priorities are shifting compared to 2019: While security is still the top priority for enterprises, and hybrid working received an understandable boost, modernizing existing technology has fallen as a priority, while adopting new technologies has grown — suggesting enterprises recognize they need completely new, modern tools in order to face the future.

■ Ways of working have changed: 88% of respondents say their digital transformation goals have fundamentally changed over the last two years; 95% have accelerated their application modernization strategies; 90% have changed the way they budget for digital transformation; and 93% say digital transformation projects over the last two years represent permanent changes to the way their business's way of operating or working.

■ End users are the focus: 88% of respondents said their digital transformation projects had been driven more by changes in user behavior than by creating new business opportunities.

Digital transformation ... needs to be the responsibility of, and driven by, the whole C-suite, rather than left solely in IT's hands

"This is an exciting time for the IT industry. We are entering a period of extreme creativity, as organizations shift from digital transformation driven by reacting to outside events, such as the pandemic or competitors' progress, to a more proactive approach driven by ideas from within the business," continued Mayuram. "For this new creativity to work, it needs to be driven from the top. Digital transformation shouldn't only be aligned to strategic goals. As a transformative business asset it needs to be the responsibility of, and driven by, the whole C-suite, rather than left solely in IT's hands. If businesses can do this and put the lessons they learned from the last two years into practice, then the future looks very bright indeed."

The Latest

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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? ...

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 ...