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Looking Ahead: Industry Predictions for 2021

Angie Mistretta
AppDynamics

This year introduced a number of new challenges for IT teams due to the influx of technology migration, increased demand for resources and rapid digital transformation caused by the COVID-19 pandemic.

The lessons we've learned in 2020 will be valuable for us to carry into the "next normal" we're expecting in 2021 and beyond, where work and life are likely permanently changed. As we reflect on the last year and begin to plan for the future, we expect to see trends like prioritization of the user experience and the dependence on IT teams continue, recognizing that what worked yesterday, may not work today or in the near future.

2020 Lessons

As the pandemic spread and people globally were forced to stay in their homes, technology became the only way many people were able to work, learn and stay connected. This put an enormous strain on IT teams to keep day-to-day life moving. As we saw in our own research, 81 percent of technologists stated the COVID-19 pandemic created the biggest technology pressure for their organization they had ever experienced and 64 percent said they were asked to perform tasks they had never done before. The pressure experienced by IT teams led to the rapid adoption of new technologies and techniques and we saw a growing interest in reducing siloed approaches to IT, with the business leaders working more closely with their teams to better understand their needs and help them resolve issues or make changes more efficiently.

The dramatic shift and dependence on technology also made IT more critical to businesses' success than ever before, especially as the digital user experience took center stage this year. The AppDynamics App Attention Index from 2019 found over the next three years, 85 percent of consumers expected to select brands on the variety of digital services they provided. Now, almost every business has had to figure out how to offer their services digitally. With 66 percent of consumers claiming they would avoid trying a brand known for delivering poor digital experience, it is vital now and into the new year that every business has strong, agile IT teams in place to keep everything running efficiently.

2021: What to Expect and How to Prepare

Looking at how the industry evolved this year to keep up with demands while delivering new experiences and innovation has taught us quite a bit. Looking forward, here are some of the changes we expect for the next year and insights on how IT leaders can prepare:

Observability will be key. Broader observability will be a strategic priority as companies develop more complex systems and expand their technology infrastructures. As businesses accelerate their digital transformation journeys in the ongoing response to the COVID-19 pandemic, their environments have become more complex than ever. By using observability solutions to pull meaningful data from logs, metrics, traces and events — developers can shift from monitoring everything, to monitoring the data and insights that will impact business outcomes most significantly.

Taking risks will be encouraged. More organizations will encourage technologists to take risks to enable more rapid transformation for the user experience. Prior to 2020, the approval process for new business strategies took a long time, but due to demands for faster, more innovative approaches this year, businesses realized they were able to adjust quickly and be more accepting of new ideas.

Prioritization of automation and cloud. IT practitioners, especially when supporting their business' migration to the cloud, need five key things to ensure the process before, during and after goes smoothly: visibility, automation, consolidation, simplification and transformation. IT teams are being asked to do more with less, and, in 2021, the automation of digital processes will be what allows them to expand into the cloud with full visibility into data obstructions and the ability to mitigate these risks in a timely manner.

An integration of security and user experience. There is a growing demand for tying security to the application and user experience, which will only continue to be a top priority in 2021. Balancing frictionless security and user experience is always a challenge, but full stack observability gives businesses the ability to see where users are hitting roadblocks and disengaging, as well as where security hurdles need to be enhanced or reduced.

It is impossible to know for certain what new challenges or opportunities 2021 will bring, but by leveraging many of the key insights from 2020, we can make it easier to adapt. Business leaders and technologists across all industries came together this year to adapt, survive and hopefully thrive — we should celebrate this alignment and growth while preparing for the future by taking on new challenges and expanding the resources available to IT teams to continue our digital transformation journeys.

Angie Mistretta is CMO of AppDynamics, a part of Cisco

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 ...

Looking Ahead: Industry Predictions for 2021

Angie Mistretta
AppDynamics

This year introduced a number of new challenges for IT teams due to the influx of technology migration, increased demand for resources and rapid digital transformation caused by the COVID-19 pandemic.

The lessons we've learned in 2020 will be valuable for us to carry into the "next normal" we're expecting in 2021 and beyond, where work and life are likely permanently changed. As we reflect on the last year and begin to plan for the future, we expect to see trends like prioritization of the user experience and the dependence on IT teams continue, recognizing that what worked yesterday, may not work today or in the near future.

2020 Lessons

As the pandemic spread and people globally were forced to stay in their homes, technology became the only way many people were able to work, learn and stay connected. This put an enormous strain on IT teams to keep day-to-day life moving. As we saw in our own research, 81 percent of technologists stated the COVID-19 pandemic created the biggest technology pressure for their organization they had ever experienced and 64 percent said they were asked to perform tasks they had never done before. The pressure experienced by IT teams led to the rapid adoption of new technologies and techniques and we saw a growing interest in reducing siloed approaches to IT, with the business leaders working more closely with their teams to better understand their needs and help them resolve issues or make changes more efficiently.

The dramatic shift and dependence on technology also made IT more critical to businesses' success than ever before, especially as the digital user experience took center stage this year. The AppDynamics App Attention Index from 2019 found over the next three years, 85 percent of consumers expected to select brands on the variety of digital services they provided. Now, almost every business has had to figure out how to offer their services digitally. With 66 percent of consumers claiming they would avoid trying a brand known for delivering poor digital experience, it is vital now and into the new year that every business has strong, agile IT teams in place to keep everything running efficiently.

2021: What to Expect and How to Prepare

Looking at how the industry evolved this year to keep up with demands while delivering new experiences and innovation has taught us quite a bit. Looking forward, here are some of the changes we expect for the next year and insights on how IT leaders can prepare:

Observability will be key. Broader observability will be a strategic priority as companies develop more complex systems and expand their technology infrastructures. As businesses accelerate their digital transformation journeys in the ongoing response to the COVID-19 pandemic, their environments have become more complex than ever. By using observability solutions to pull meaningful data from logs, metrics, traces and events — developers can shift from monitoring everything, to monitoring the data and insights that will impact business outcomes most significantly.

Taking risks will be encouraged. More organizations will encourage technologists to take risks to enable more rapid transformation for the user experience. Prior to 2020, the approval process for new business strategies took a long time, but due to demands for faster, more innovative approaches this year, businesses realized they were able to adjust quickly and be more accepting of new ideas.

Prioritization of automation and cloud. IT practitioners, especially when supporting their business' migration to the cloud, need five key things to ensure the process before, during and after goes smoothly: visibility, automation, consolidation, simplification and transformation. IT teams are being asked to do more with less, and, in 2021, the automation of digital processes will be what allows them to expand into the cloud with full visibility into data obstructions and the ability to mitigate these risks in a timely manner.

An integration of security and user experience. There is a growing demand for tying security to the application and user experience, which will only continue to be a top priority in 2021. Balancing frictionless security and user experience is always a challenge, but full stack observability gives businesses the ability to see where users are hitting roadblocks and disengaging, as well as where security hurdles need to be enhanced or reduced.

It is impossible to know for certain what new challenges or opportunities 2021 will bring, but by leveraging many of the key insights from 2020, we can make it easier to adapt. Business leaders and technologists across all industries came together this year to adapt, survive and hopefully thrive — we should celebrate this alignment and growth while preparing for the future by taking on new challenges and expanding the resources available to IT teams to continue our digital transformation journeys.

Angie Mistretta is CMO of AppDynamics, a part of Cisco

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 ...