Gartner: Top Trends Impacting Infrastructure and Operations for 2022

Gartner highlighted 6 trends that infrastructure and operations (I&O) leaders must start preparing for in the next 12-18 months.

"I&O leaders need to drive change, not simply absorb it," said Jeffrey Hewitt, Research VP at Gartner. "They are expected to deliver more adaptable and resilient service from anywhere — and for an increasingly distributed workforce. This is pressuring I&O to take actions that will tie their decisions more closely to business requirements, a theme that runs through this year's trends."

Here are the top trends impacting I&O in 2022:

Trend 1: Just-In-Time Infrastructure

The speed at which infrastructure can be deployed is becoming just as important as putting the right infrastructure in the right place — colocation, data center, at the edge and more. This is the idea behind just-in-time infrastructure.

Borrowed from the term "just-in-time manufacturing," this trend aims to reduce infrastructure deployment times as well as fuel enterprise responsiveness to business needs and anywhere operations. Gartner expects it to be a differentiating factor when enterprises compare and negotiate with service providers moving forward.

Trend 2: Digital Natives

Digital-native companies are those that made public cloud and other digital capabilities part of their business model from the start, such as ride sharing applications or digital food delivery services. They combine different revenue approaches to monetize digital assets to gain new customers and boost market share and have only become more commonplace since the onset of the pandemic.

"There is an opportunity for traditional I&O organizations to leverage their digital-native counterparts that thrived during the pandemic to also produce highly agile, innovative and competitive offerings themselves, or join those that can," said Hewitt. "I&O leaders are faced with a "join or compete" dilemma."

By 2025, 70% of I&O leaders who ignore innovation will be marginalized to legacy system support only.

Trend 3: Management Confluence

This trend reflects the need for the growing number of management and monitoring tools — from IT service management (ITSM) to artificial intelligence operations (AIOps) and more — to be brought together in a single, comprehensive tool. Such integration is indispensable in the adoption of composable technologies, one of the three domains of business composability, which allows components of systems and data to combine more quickly and easily.

According to the 2022 Gartner CIO and Technology Executive Survey, 58% of high-composability enterprises build out integration capabilities for data, analytics and applications. These organizations reported better business performance compared with peers or competitors in the past year.

"I&O leaders can extend composability throughout the entire technology stack by inventorying their current management tool usage and identifying those that can be combined to form a more valuable, all-inclusive portfolio that improves I&O agility and drives optimal business results," said Hewitt.

Trend 4: Data Proliferation

Data will continue to multiply in variety, velocity and volume. As businesses continue to expand their data collection and holding efforts, I&O will be instrumental in guiding the policies surrounding processing, retention and legal requirements of the enterprise's data.

"I&O workforces need to work closely with their chief data officer to expand data literacy and effectively support data management across the enterprise," said Hewitt.

Trend 5: Business Acumen

I&O leaders are guiding their functions through a rapidly changing and distributed technology environment, which is threatened by the IT talent gap and requires new skills. According to a recent Gartner survey, 64% of I&O leaders point to insufficient skills and resources as one of their greatest challenges this past year.

"Technical skills' shelf life is shortening," said Hewitt. "As the I&O function is asked to provide more business justification for what they do, organizations are looking for I&O new hires to have business backgrounds rather than strictly technical degrees."

Gartner expects that by 2025, CIOs will fill 65% of open I&O leader positions with people that have no I&O experience.

Trend 6: Career Ladders to Career Lattices

Similar to the business acumen trend, I&O is moving away from single domain career paths driven by workloads and legacy technical skills. In fact, 29% of the skills in an average I&O job posting in 2018 will not be needed by 2022, according to Gartner Talent Neuron data.

Instead, I&O teams are moving laterally across a competency-based lattice that takes into account softer skills and emphasizes both learning agility and cross-domain expertise.

"While this certainly requires a mindset adjustment for some of the more tenured I&O workers, there will be much more opportunity within I&O teams as they move away from territorial thinking and toward fostering a collaborative environment," said Hewitt.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

Gartner: Top Trends Impacting Infrastructure and Operations for 2022

Gartner highlighted 6 trends that infrastructure and operations (I&O) leaders must start preparing for in the next 12-18 months.

"I&O leaders need to drive change, not simply absorb it," said Jeffrey Hewitt, Research VP at Gartner. "They are expected to deliver more adaptable and resilient service from anywhere — and for an increasingly distributed workforce. This is pressuring I&O to take actions that will tie their decisions more closely to business requirements, a theme that runs through this year's trends."

Here are the top trends impacting I&O in 2022:

Trend 1: Just-In-Time Infrastructure

The speed at which infrastructure can be deployed is becoming just as important as putting the right infrastructure in the right place — colocation, data center, at the edge and more. This is the idea behind just-in-time infrastructure.

Borrowed from the term "just-in-time manufacturing," this trend aims to reduce infrastructure deployment times as well as fuel enterprise responsiveness to business needs and anywhere operations. Gartner expects it to be a differentiating factor when enterprises compare and negotiate with service providers moving forward.

Trend 2: Digital Natives

Digital-native companies are those that made public cloud and other digital capabilities part of their business model from the start, such as ride sharing applications or digital food delivery services. They combine different revenue approaches to monetize digital assets to gain new customers and boost market share and have only become more commonplace since the onset of the pandemic.

"There is an opportunity for traditional I&O organizations to leverage their digital-native counterparts that thrived during the pandemic to also produce highly agile, innovative and competitive offerings themselves, or join those that can," said Hewitt. "I&O leaders are faced with a "join or compete" dilemma."

By 2025, 70% of I&O leaders who ignore innovation will be marginalized to legacy system support only.

Trend 3: Management Confluence

This trend reflects the need for the growing number of management and monitoring tools — from IT service management (ITSM) to artificial intelligence operations (AIOps) and more — to be brought together in a single, comprehensive tool. Such integration is indispensable in the adoption of composable technologies, one of the three domains of business composability, which allows components of systems and data to combine more quickly and easily.

According to the 2022 Gartner CIO and Technology Executive Survey, 58% of high-composability enterprises build out integration capabilities for data, analytics and applications. These organizations reported better business performance compared with peers or competitors in the past year.

"I&O leaders can extend composability throughout the entire technology stack by inventorying their current management tool usage and identifying those that can be combined to form a more valuable, all-inclusive portfolio that improves I&O agility and drives optimal business results," said Hewitt.

Trend 4: Data Proliferation

Data will continue to multiply in variety, velocity and volume. As businesses continue to expand their data collection and holding efforts, I&O will be instrumental in guiding the policies surrounding processing, retention and legal requirements of the enterprise's data.

"I&O workforces need to work closely with their chief data officer to expand data literacy and effectively support data management across the enterprise," said Hewitt.

Trend 5: Business Acumen

I&O leaders are guiding their functions through a rapidly changing and distributed technology environment, which is threatened by the IT talent gap and requires new skills. According to a recent Gartner survey, 64% of I&O leaders point to insufficient skills and resources as one of their greatest challenges this past year.

"Technical skills' shelf life is shortening," said Hewitt. "As the I&O function is asked to provide more business justification for what they do, organizations are looking for I&O new hires to have business backgrounds rather than strictly technical degrees."

Gartner expects that by 2025, CIOs will fill 65% of open I&O leader positions with people that have no I&O experience.

Trend 6: Career Ladders to Career Lattices

Similar to the business acumen trend, I&O is moving away from single domain career paths driven by workloads and legacy technical skills. In fact, 29% of the skills in an average I&O job posting in 2018 will not be needed by 2022, according to Gartner Talent Neuron data.

Instead, I&O teams are moving laterally across a competency-based lattice that takes into account softer skills and emphasizes both learning agility and cross-domain expertise.

"While this certainly requires a mindset adjustment for some of the more tenured I&O workers, there will be much more opportunity within I&O teams as they move away from territorial thinking and toward fostering a collaborative environment," said Hewitt.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...