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How Enterprises Can Get Through Digital Transformation Gridlock

Gustavo Gómez

The modern customer has come to expect a unique user experience with an emphasis on mobile and digital accessibility. In fact, a recent study, The Agility Trap, conducted by Bizagi, revealed that 79 percent of businesses with high levels of digital change cite changing customer expectations as the key driver for transformation. But that transformation is no easy task. Only 25 percent of businesses globally are highly agile, revealing that there is room for improvement across regions when it comes to incorporating fresh strategies and processes.

Companies need to make a big leap forward in digital to gain a competitive edge before they are too far behind to play catch-up. After all, 75 percent of respondents think that providing a customer experience that meets the immediate needs and reflects the circumstances of the individual is key to staying ahead of the pack.

That being said, the research also revealed that 87 percent of businesses still find digital transformation to be a strategic challenge, in which they get stuck in an "agility trap." An agility trap occurs when businesses seeking rapid digital transformation come out of the gate too quickly and get stuck due to organizational or technological complexity. Fortunately, if businesses recognize the common risk factors and develop a plan accordingly, they can avoid these all too common pitfalls.

Understanding Company Weaknesses

Businesses embarking on a digital transformation journey often come across several warning signs that, when ignored, can spell disaster. Failing to identify the following risk factors and address them internally can slow down digital transformation or bring the entire process to a standstill:

1. Lack of internal collaboration: In order to kick-start an external digital transformation, internal teams need to be on board. Driving change across the employee and internal user base is one of the key "transformation drivers," but it can easily be derailed by a lack of collaboration within a business. Over 50 percent of survey respondents believe that they are either resistant to or have mixed views towards transformation and change, which multiply the chances of hitting roadblocks during the process.

2. Lack of leadership knowledge: Transformation strategies are often formed at the leadership level where customer expectations are analyzed. However, leadership often lacks the necessary knowledge of internal processes to develop a strategy and pass it down to others in the organization, thereby halting the process before it even begins. Instead, organizations should approach digital transformation by building an integrated team with stakeholders from a range of levels.

3. Lack of agility in IT: Finally, one of the greatest risk factors is a lack of agility within the IT department. If IT leadership is unable to rapidly and easily incorporate new internal technologies and methods, or respond to changing business conditions in a timely manner, it can pull an entire business into a digital transformation slump.

Overcoming Cultural Resistance to Change

Every business has a unique corporate culture, but an overwhelming number of businesses encounter cultural resistance along their path to digitize. For as many people in support of transformation and change, there are nearly as many who are hesitant and view change as a threat.

The research revealed that even when many digital projects are already in place, 44 percent of respondents said that there was still internal resistance at play. Change can be risky, but when it comes to digital transformation, meeting customer expectations and keeping up with industry trends is worth the gamble.

Planning the Path to Success

In order to ignite a successful digital transformation, businesses need to recognize the risks and avoid those pitfalls along the way, all while keeping success factors and benchmarks in mind. Turning a potential agility trap into an "ignition switch" for transformation strategy can keep a business on track. Looking at the potential risks, the ignition switches businesses need to turn on are strategic clarity, responsive processes and business alignment.

It is impossible to mitigate all risks before embarking on a program of systemic change, therefore, a business must be able bend and pivot in response to unexpected issues that arise with budget, leadership engagement or internal rifts. Collaboration needs to occur across traditional organizational "silos." When IT leaders and members of the executive suite align on their overall vision and transformation tactics, they create the healthy environment that's required to evolve for digital business.

Gustavo Gómez is CEO of Bizagi.

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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 ...

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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 ...

How Enterprises Can Get Through Digital Transformation Gridlock

Gustavo Gómez

The modern customer has come to expect a unique user experience with an emphasis on mobile and digital accessibility. In fact, a recent study, The Agility Trap, conducted by Bizagi, revealed that 79 percent of businesses with high levels of digital change cite changing customer expectations as the key driver for transformation. But that transformation is no easy task. Only 25 percent of businesses globally are highly agile, revealing that there is room for improvement across regions when it comes to incorporating fresh strategies and processes.

Companies need to make a big leap forward in digital to gain a competitive edge before they are too far behind to play catch-up. After all, 75 percent of respondents think that providing a customer experience that meets the immediate needs and reflects the circumstances of the individual is key to staying ahead of the pack.

That being said, the research also revealed that 87 percent of businesses still find digital transformation to be a strategic challenge, in which they get stuck in an "agility trap." An agility trap occurs when businesses seeking rapid digital transformation come out of the gate too quickly and get stuck due to organizational or technological complexity. Fortunately, if businesses recognize the common risk factors and develop a plan accordingly, they can avoid these all too common pitfalls.

Understanding Company Weaknesses

Businesses embarking on a digital transformation journey often come across several warning signs that, when ignored, can spell disaster. Failing to identify the following risk factors and address them internally can slow down digital transformation or bring the entire process to a standstill:

1. Lack of internal collaboration: In order to kick-start an external digital transformation, internal teams need to be on board. Driving change across the employee and internal user base is one of the key "transformation drivers," but it can easily be derailed by a lack of collaboration within a business. Over 50 percent of survey respondents believe that they are either resistant to or have mixed views towards transformation and change, which multiply the chances of hitting roadblocks during the process.

2. Lack of leadership knowledge: Transformation strategies are often formed at the leadership level where customer expectations are analyzed. However, leadership often lacks the necessary knowledge of internal processes to develop a strategy and pass it down to others in the organization, thereby halting the process before it even begins. Instead, organizations should approach digital transformation by building an integrated team with stakeholders from a range of levels.

3. Lack of agility in IT: Finally, one of the greatest risk factors is a lack of agility within the IT department. If IT leadership is unable to rapidly and easily incorporate new internal technologies and methods, or respond to changing business conditions in a timely manner, it can pull an entire business into a digital transformation slump.

Overcoming Cultural Resistance to Change

Every business has a unique corporate culture, but an overwhelming number of businesses encounter cultural resistance along their path to digitize. For as many people in support of transformation and change, there are nearly as many who are hesitant and view change as a threat.

The research revealed that even when many digital projects are already in place, 44 percent of respondents said that there was still internal resistance at play. Change can be risky, but when it comes to digital transformation, meeting customer expectations and keeping up with industry trends is worth the gamble.

Planning the Path to Success

In order to ignite a successful digital transformation, businesses need to recognize the risks and avoid those pitfalls along the way, all while keeping success factors and benchmarks in mind. Turning a potential agility trap into an "ignition switch" for transformation strategy can keep a business on track. Looking at the potential risks, the ignition switches businesses need to turn on are strategic clarity, responsive processes and business alignment.

It is impossible to mitigate all risks before embarking on a program of systemic change, therefore, a business must be able bend and pivot in response to unexpected issues that arise with budget, leadership engagement or internal rifts. Collaboration needs to occur across traditional organizational "silos." When IT leaders and members of the executive suite align on their overall vision and transformation tactics, they create the healthy environment that's required to evolve for digital business.

Gustavo Gómez is CEO of Bizagi.

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 ...