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Hybrid and Remote Work Increases Workloads and Poses Challenges to Remote Network Experiences

87% of organizations allocated budgets to update network tools for remote and hybrid users, but only 32% have been successful

The ongoing shift to hybrid and remote work environments has resulted in key changes to the roles and priorities of network administrators in order to address new connectivity challenges and prioritize and preserve a secure, productive end-user experience, according to new research by Enterprise Management Associates (EMA) and Auvik.

The report examined the remote and hybrid work paradigm through the lens of network operations teams — 73% of which reported an increase in workloads, either slightly or significantly, following the shift from traditional to hybrid work environments.

In Episode 2 of the MEAN TIME TO INSIGHT Podcast, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA, discusses the network management impacts of remote work.

Click here for a direct MP3 download of Episode 2

Results from the report demonstrate that the top challenges associated with the remote work experience are poor home Wi-Fi setups, distance from applications, and poor ISP quality.

To combat these obstacles, 72% of surveyed organizations have deployed network hardware to the homes of remote workers, including network security devices (62.7%) and Wi-Fi access points (54.1%).

Additionally, 90% of organizations with hybrid workers shared that they had to upgrade Wi-Fi networks to address increased office mobility requirements.

"These results reinforce that although people are beginning to return to the office, hybrid work is here to stay and is resulting in significant changes for network administrators," said Alex Hoff, Co-Founder and Chief Strategy Officer for Auvik. "Although IT teams no longer own all the assets utilized daily by employees, they are still responsible for these operations. And despite not being able to directly exert control over employees' home networks, they can have visibility over these environments with network monitoring tools. Implementing network visibility software helps IT professionals overcome these new obstacles by providing the ability to maintain visibility and control amid changing work circumstances."

Additional findings from the report include:

■ Nearly 49% of network operations teams started working with a new tool vendor to help them manage the network experience of remote workers.

■ 76% of organizations need to unify how they manage network access policies across on-premises networks and remote users.

■ Remote desktop access tools (deployed by 81% of companies) remain the go-to solution for troubleshooting remote users' problems, but endpoint monitoring tools are increasingly popular (79%).

■ Although 87% have allocated funds in their budget to update network operation tools for remote and hybrid user support, only 32% of organizations shared that they have been successful in doing so.

■ The top issues employees most often report when they are working from home are VPN access issues, followed by performance issues with SaaS applications.

"96% of IT organizations said they are supporting hybrid workers, and 30% of all employees who work remotely are hybrid workers," said Shamus McGillicuddy, VP of Research, EMA. "With employees working both at home and in the office, it is important to have the assets and software necessary to support them in both locations. This means enterprises must invest in more secure remote access solutions that offer integrated network security automation, centralized management, and network optimization or network enhancement, as well as network observability tools that are able to monitor performance across disparate locations."

Methodology: Auvik commissioned EMA, an independent research firm, to survey 354 IT professionals directly involved in supporting the networking requirements of employees who work from home.

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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 ...

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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 ...

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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? ...

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Hybrid and Remote Work Increases Workloads and Poses Challenges to Remote Network Experiences

87% of organizations allocated budgets to update network tools for remote and hybrid users, but only 32% have been successful

The ongoing shift to hybrid and remote work environments has resulted in key changes to the roles and priorities of network administrators in order to address new connectivity challenges and prioritize and preserve a secure, productive end-user experience, according to new research by Enterprise Management Associates (EMA) and Auvik.

The report examined the remote and hybrid work paradigm through the lens of network operations teams — 73% of which reported an increase in workloads, either slightly or significantly, following the shift from traditional to hybrid work environments.

In Episode 2 of the MEAN TIME TO INSIGHT Podcast, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA, discusses the network management impacts of remote work.

Click here for a direct MP3 download of Episode 2

Results from the report demonstrate that the top challenges associated with the remote work experience are poor home Wi-Fi setups, distance from applications, and poor ISP quality.

To combat these obstacles, 72% of surveyed organizations have deployed network hardware to the homes of remote workers, including network security devices (62.7%) and Wi-Fi access points (54.1%).

Additionally, 90% of organizations with hybrid workers shared that they had to upgrade Wi-Fi networks to address increased office mobility requirements.

"These results reinforce that although people are beginning to return to the office, hybrid work is here to stay and is resulting in significant changes for network administrators," said Alex Hoff, Co-Founder and Chief Strategy Officer for Auvik. "Although IT teams no longer own all the assets utilized daily by employees, they are still responsible for these operations. And despite not being able to directly exert control over employees' home networks, they can have visibility over these environments with network monitoring tools. Implementing network visibility software helps IT professionals overcome these new obstacles by providing the ability to maintain visibility and control amid changing work circumstances."

Additional findings from the report include:

■ Nearly 49% of network operations teams started working with a new tool vendor to help them manage the network experience of remote workers.

■ 76% of organizations need to unify how they manage network access policies across on-premises networks and remote users.

■ Remote desktop access tools (deployed by 81% of companies) remain the go-to solution for troubleshooting remote users' problems, but endpoint monitoring tools are increasingly popular (79%).

■ Although 87% have allocated funds in their budget to update network operation tools for remote and hybrid user support, only 32% of organizations shared that they have been successful in doing so.

■ The top issues employees most often report when they are working from home are VPN access issues, followed by performance issues with SaaS applications.

"96% of IT organizations said they are supporting hybrid workers, and 30% of all employees who work remotely are hybrid workers," said Shamus McGillicuddy, VP of Research, EMA. "With employees working both at home and in the office, it is important to have the assets and software necessary to support them in both locations. This means enterprises must invest in more secure remote access solutions that offer integrated network security automation, centralized management, and network optimization or network enhancement, as well as network observability tools that are able to monitor performance across disparate locations."

Methodology: Auvik commissioned EMA, an independent research firm, to survey 354 IT professionals directly involved in supporting the networking requirements of employees who work from home.

Hot Topics

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 ...