2022 Digital Transformation Predictions

As part of 2022 APM Predictions list, APMdigest asked industry experts to predict how Digital Transformation will evolve and impact business in 2022.

Digital Transformation Projects Accelerate

According to IDC, by 2022, 70% of all organizations will have accelerated use of digital technologies, transforming existing business processes to drive customer engagement, employee productivity, and business resiliency. As we saw the pandemic accelerate remote working, there is not much sign of things returning to normal any time soon. In 2022, we will see an increase in digital transformation projects that provide better collaboration across multi-functional teams, requiring stricter data governance and tighter security, while providing cost and performance-optimized hybrid data infrastructures.
Venkat Rajaji
VP Product Management, Quest Software

As 2022 approaches, the pace of digital transformation in enterprises will accelerate. With more applications moving to containers and Kubernetes, legacy storage data management platforms built to support monoliths won't be able to provide the scalability and granularity to successfully manage data for larger distributed microservices based applications. In addition, the need for agility and speed in building and deploying applications will become more significant, which is where containers will be the best options for optimal scalability and adaptability for rapid data delivery.
Kirby Wadsworth
CMO, ionir

Next-Gen of Digital Transformation is Digital Automation

In 2022, we'll see industries incorporate automation into their digital transformation strategies. Digital transformation has been a mainstay in the marketplace for a while now, and the progress and escalation due to the pandemic and our remote world have many marketplaces providing automation for the digitalization of automation. In the wake of successful digital transformation, we'll see automation begin to touch all facets of businesses for automation in fulfillment, accounting, advertising and marketing. This concept will percolate for the SMB with customer relationship automation, which I anticipate where we'll see the most growth in the next decade.
Borya Shakhnovich
CEO, airSlate

HYPERAUTOMATION REPLACES AUTOMATION

Hyperautomation will replace automation as the next business imperative for organizations undergoing digital transformation. Advances in automation have created operational efficiencies, but these automations are typically static. If processes, workflows, apps or data change, developers must update their automations — essentially turning an automated process intto a manual one. Hyperautomation, on the other hand, uses AI/ML to identify patterns to create smarter automations that can evolve and adapt to change at the speed and scale businesses need now.
Ed Macosky
SVP and Head of Product, Boomi

CEO becomes more technical

Digital business has been our reality for several years now, but the pandemic completely cemented that reality for businesses. While it used to be that CFOs and the finance organization influenced core business strategy, now it's the software side that dictates strategy. For example, if the C-level executives don't understand software development, then M&A opportunities will suffer and silos will pop up throughout a business — burdening the entire organization and limiting customer success. Moving forward, we'll see CEOs grow their technical acumen and install digital board members with non-traditional software backgrounds to succeed in the digital world.
Derek Holt
GM of Agile and DevOps, Digital.ai

RESISTANCE TO CHANGE HINDERS DIGITAL TRANSFORMATION

Organizational change and resistance of IT organizations/staff to adopt new models (e.g. project-to-product thinking) will continue to be the #1 impediment for companies attempting to achieve their digital transformation goals.
Julian Dunn
Director of Product Marketing, PagerDuty

Recovery From Failed and Flawed Transformations

The pandemic made digital transformation a business mandate for every type of organization, everywhere, all at the same time. From SMBs to huge enterprises, everyone raced to adopt new digital tools to support new ways of working and of reaching customers. In the rush, many of these transformations failed, or were implemented without reaching their full impact. Organizations who underwent digital transformation in 2020 and 2021 will look back in 2022 to measure their success — and, given that pre-pandemic upwards of 80% of digital transformations may have failed — they will likely discover significant room for improvement. As a result, in 2022 we will see the c-suite questioning IT on the value of tech investments and tech teams, and in turn, optimizing and implementing more new approaches and platforms throughout their stacks.
Tej Redkar
Chief Product Officer, LogicMonitor

Related Links

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Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

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 ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

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 ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

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 ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

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 ...

Explainability Is the New Battleground in AI-Powered Observability

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 ...

Empowering the Human Side of the Autonomous IT Age

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 Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

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.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

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 ...

2022 Digital Transformation Predictions

As part of 2022 APM Predictions list, APMdigest asked industry experts to predict how Digital Transformation will evolve and impact business in 2022.

Digital Transformation Projects Accelerate

According to IDC, by 2022, 70% of all organizations will have accelerated use of digital technologies, transforming existing business processes to drive customer engagement, employee productivity, and business resiliency. As we saw the pandemic accelerate remote working, there is not much sign of things returning to normal any time soon. In 2022, we will see an increase in digital transformation projects that provide better collaboration across multi-functional teams, requiring stricter data governance and tighter security, while providing cost and performance-optimized hybrid data infrastructures.
Venkat Rajaji
VP Product Management, Quest Software

As 2022 approaches, the pace of digital transformation in enterprises will accelerate. With more applications moving to containers and Kubernetes, legacy storage data management platforms built to support monoliths won't be able to provide the scalability and granularity to successfully manage data for larger distributed microservices based applications. In addition, the need for agility and speed in building and deploying applications will become more significant, which is where containers will be the best options for optimal scalability and adaptability for rapid data delivery.
Kirby Wadsworth
CMO, ionir

Next-Gen of Digital Transformation is Digital Automation

In 2022, we'll see industries incorporate automation into their digital transformation strategies. Digital transformation has been a mainstay in the marketplace for a while now, and the progress and escalation due to the pandemic and our remote world have many marketplaces providing automation for the digitalization of automation. In the wake of successful digital transformation, we'll see automation begin to touch all facets of businesses for automation in fulfillment, accounting, advertising and marketing. This concept will percolate for the SMB with customer relationship automation, which I anticipate where we'll see the most growth in the next decade.
Borya Shakhnovich
CEO, airSlate

HYPERAUTOMATION REPLACES AUTOMATION

Hyperautomation will replace automation as the next business imperative for organizations undergoing digital transformation. Advances in automation have created operational efficiencies, but these automations are typically static. If processes, workflows, apps or data change, developers must update their automations — essentially turning an automated process intto a manual one. Hyperautomation, on the other hand, uses AI/ML to identify patterns to create smarter automations that can evolve and adapt to change at the speed and scale businesses need now.
Ed Macosky
SVP and Head of Product, Boomi

CEO becomes more technical

Digital business has been our reality for several years now, but the pandemic completely cemented that reality for businesses. While it used to be that CFOs and the finance organization influenced core business strategy, now it's the software side that dictates strategy. For example, if the C-level executives don't understand software development, then M&A opportunities will suffer and silos will pop up throughout a business — burdening the entire organization and limiting customer success. Moving forward, we'll see CEOs grow their technical acumen and install digital board members with non-traditional software backgrounds to succeed in the digital world.
Derek Holt
GM of Agile and DevOps, Digital.ai

RESISTANCE TO CHANGE HINDERS DIGITAL TRANSFORMATION

Organizational change and resistance of IT organizations/staff to adopt new models (e.g. project-to-product thinking) will continue to be the #1 impediment for companies attempting to achieve their digital transformation goals.
Julian Dunn
Director of Product Marketing, PagerDuty

Recovery From Failed and Flawed Transformations

The pandemic made digital transformation a business mandate for every type of organization, everywhere, all at the same time. From SMBs to huge enterprises, everyone raced to adopt new digital tools to support new ways of working and of reaching customers. In the rush, many of these transformations failed, or were implemented without reaching their full impact. Organizations who underwent digital transformation in 2020 and 2021 will look back in 2022 to measure their success — and, given that pre-pandemic upwards of 80% of digital transformations may have failed — they will likely discover significant room for improvement. As a result, in 2022 we will see the c-suite questioning IT on the value of tech investments and tech teams, and in turn, optimizing and implementing more new approaches and platforms throughout their stacks.
Tej Redkar
Chief Product Officer, LogicMonitor

Related Links

Hot Topics

The Latest

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

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 ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

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 ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

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 ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

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 ...

Explainability Is the New Battleground in AI-Powered Observability

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 ...

Empowering the Human Side of the Autonomous IT Age

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 Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

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.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

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 ...