Tech Disruptions Cost Companies Millions of Dollars in Lost Productivity Annually

Learn more about Ivanti

Over the next three years, 92% of companies plan to increase their AI investments, according to McKinsey. However, Ivanti's 2025 Digital Employee Experience (DEX) Report shows that just 21% of office workers say AI is significantly improving their productivity.

In the age of AI, digital friction threatens to undermine AI's potential, exacerbate tech problems and have a corrosive effect on employee productivity. Office workers already endure 3.6 tech interruptions and 2.7 security update disruptions per month. This equates to nearly $4 million in lost productivity annually for a company with 2,000 employees.

The number of workplace tools is exploding faster than employees can master them, yet nearly half of office workers say they're left to teach themselves how to use new technology — a source of frustration for employees and inefficiency for the business. For instance, among the 93% of companies that haven't banned AI use, only 40% have provided training, while another 24% plan to offer it soon.

"As organizations accelerate their AI investments, it's clear that realizing AI's promise requires a deeper understanding of the employee experience and impact on productivity. Tools that monitor and analyze how employees interact with technology in real time, like Digital Employee Experience (DEX) solutions, offer data-driven insights – revealing workflow bottlenecks and initiating self-healing actions," said Dennis Kozak, CEO of Ivanti. "By embracing DEX, organizations can take their AI initiatives further and truly empower their workforce, moving from reactive problem-solving to proactive improvement. DEX is more than a strategy for improving the employee experience; it's the engine that embeds AI into company culture, productivity and daily operations."

Additional key findings from the report include:

The newest office perk is employee technology autonomy

A new frontier in workplace benefits is emerging, giving employees greater autonomy over their technology. On average, office workers rate their workplace tools at just a "B-." Tellingly, 65% report that frustrations with these tools can negatively affect their mood and morale. Device choice is also a pressing concern; while 67% note that having a say in the devices they use is important, only 36% currently enjoy this freedom.

The help desk is evolving thanks to AI

AI is transforming help desks, moving them beyond the break-fix cycle that has defined IT support for decades. While most companies have automated basic IT operations such as security patch management (72%) and IT ticket routing (67%), significant opportunities remain. Nearly 40% still haven't automated password resets, missing an easy win that could eliminate countless routine support tickets.

As AI adoption accelerates, organizations must move beyond piecemeal DEX adoption and invest in strategies that deliver measurable improvements to both employee satisfaction and the bottom line.

Hot Topics

The Latest

Escaping Pilot Purgatory: How AI Becomes an Operational Advantage

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.

Tech Disruptions Cost Companies Millions of Dollars in Lost Productivity Annually

Learn more about Ivanti

Over the next three years, 92% of companies plan to increase their AI investments, according to McKinsey. However, Ivanti's 2025 Digital Employee Experience (DEX) Report shows that just 21% of office workers say AI is significantly improving their productivity.

In the age of AI, digital friction threatens to undermine AI's potential, exacerbate tech problems and have a corrosive effect on employee productivity. Office workers already endure 3.6 tech interruptions and 2.7 security update disruptions per month. This equates to nearly $4 million in lost productivity annually for a company with 2,000 employees.

The number of workplace tools is exploding faster than employees can master them, yet nearly half of office workers say they're left to teach themselves how to use new technology — a source of frustration for employees and inefficiency for the business. For instance, among the 93% of companies that haven't banned AI use, only 40% have provided training, while another 24% plan to offer it soon.

"As organizations accelerate their AI investments, it's clear that realizing AI's promise requires a deeper understanding of the employee experience and impact on productivity. Tools that monitor and analyze how employees interact with technology in real time, like Digital Employee Experience (DEX) solutions, offer data-driven insights – revealing workflow bottlenecks and initiating self-healing actions," said Dennis Kozak, CEO of Ivanti. "By embracing DEX, organizations can take their AI initiatives further and truly empower their workforce, moving from reactive problem-solving to proactive improvement. DEX is more than a strategy for improving the employee experience; it's the engine that embeds AI into company culture, productivity and daily operations."

Additional key findings from the report include:

The newest office perk is employee technology autonomy

A new frontier in workplace benefits is emerging, giving employees greater autonomy over their technology. On average, office workers rate their workplace tools at just a "B-." Tellingly, 65% report that frustrations with these tools can negatively affect their mood and morale. Device choice is also a pressing concern; while 67% note that having a say in the devices they use is important, only 36% currently enjoy this freedom.

The help desk is evolving thanks to AI

AI is transforming help desks, moving them beyond the break-fix cycle that has defined IT support for decades. While most companies have automated basic IT operations such as security patch management (72%) and IT ticket routing (67%), significant opportunities remain. Nearly 40% still haven't automated password resets, missing an easy win that could eliminate countless routine support tickets.

As AI adoption accelerates, organizations must move beyond piecemeal DEX adoption and invest in strategies that deliver measurable improvements to both employee satisfaction and the bottom line.

Hot Topics

The Latest

Escaping Pilot Purgatory: How AI Becomes an Operational Advantage

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.