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The Path to Technojoy: How to Tackle the Silent Drivers of Technostress

Jon Mort
The Adaptavist Group

Technology's role in the workplace has expanded rapidly, framing how we work and communicate. Now, with the explosion of new and innovative AI-driven tools, people are struggling to navigate how to work in this new emergent era. And although the majority of these applications are designed to make our lives easier, for many knowledge workers, they've become a source of stress and anxiety. "Technostress," a term coined by psychoanalyst Craig Brod in 1984, describes the feelings of being overwhelmed by constant connectivity and cognitive overload from information and notifications, and it's on the rise.

Adaptavist's latest report The human cost of digital transformation, helps paint a more detailed picture. Over the last year, 64% of workers said technology had negatively impacted their lives at work, revealing how deeply embedded technostress has become in our professional lives. Nearly 1 in 3 people pointed to the volume of notifications or the burden of using multiple platforms as key stress drivers.

The sheer scale of this challenge means the consequences extend beyond individual well-being. Technostress is also having a measurable impact on global productivity; Gallup reports that declining employee engagement in 2024 may have cost the global economy as much as $438 billion in lost productivity.

The data suggest that the organizations suffering most are those with poor tool implementation, inadequate training, and weak workplace cultures. So, plotting the path to technojoy (the antidote to technostress) begins with understanding the real needs of your workforce, implementing proper tool training and creating a culture where feedback is not only encouraged but implemented. Organizations that prioritize these elements are seeing their employees embrace technology as an enabler of success, not a burden.

Meanwhile, failure to do so opens businesses up to a workforce increasingly plagued by sickness leave, absenteeism, and high turnover rates.

What's Causing Technostress?

Today's workplaces are defined by digital communication, constant connectivity, and the rise of AI tools. Face-to-face conversations have been replaced by online messages, where tone and intent is harder to read. Employees are juggling meetings and notifications across countless platforms, and are often feeling the pressure to stay connected outside of work hours. One in five workers said messages from colleagues make them feel excluded or incompetent, and a further 28% worried that their tone is easily misinterpreted in online interactions. Together, all these factors create the perfect breeding ground for technostress.

One major driver is insufficient training. With organizations finding their feet as early adopters of these new tools, a fifth of knowledge workers said a lack of guidance on new tools heightens their stress, forcing them to learn through trial and error.

Fueling anxiety and workplace pressure, these demands can be detrimental to employees' mental health and, therefore, workplace relationships and engagement. In fact, a recent study by AI note-taking tool Notta revealed that as many as 42% of workers felt that poor communication affected cross-functional collaboration, suggesting that when tools create friction, it can lead to confusion, anxiety, and a gradual breakdown of team cohesion.

The Symptoms of Technostress

As they play out at work, these shifts are leading to new challenges. Technostress doesn't just affect mental well-being; it can manifest physically, too, with research linking it to headaches, eye strain and a disrupted sleep pattern. Over time, these symptoms can transform into mental fatigue, frustration, and disengagement at work.

The business impact is equally significant. In fact, technostress has become a silent productivity killer, with studies showing employees lose the equivalent of a full working day every month due to dissatisfaction at work, leading to mental disengagement and disempowerment. A blind spot for many leaders is their underestimation of how technology affects employee experience and well-being. Workers feeling overwhelmed by technology are more likely to switch off, underperform, or quietly look for new roles.

These effects are already visible. Around 23% of knowledge workers looked for a new job in the last 12 months, while 12% have taken sick leave or time off work due to technology-related stress. 5% even quit their roles entirely. Given that there are over one billion knowledge workers globally (Gartner), this could translate to 50 million resignations and 120 million job searches each year, an alarming sign of how unchecked technostress could fuel a mass exodus of workers.

What Determines This Impact

The extent to which organizations are affected depends largely on factors like employee happiness, workplace culture, and access to proper training and support. When employees feel supported and energized by their work environment, they report an overwhelmingly positive experience with technology.

60% of workers who said they were supported by a positive workplace culture reported that technology had significantly supported their career advancement and, consequently, improved their satisfaction at work. More than 90% also said that their team integrated technology effectively into collaborative work..

Ultimately, technology alone doesn't solve problems; people do. Without the right structures, digital tools can overwhelm rather than empower. But with the right culture in place, technology becomes what it's meant to be: a catalyst for better work, not the cause of stress and burnout.

Practical Steps Towards Technojoy

If technostress thrives amid poor technology implementation, lack of training, and unsupportive cultures, then technojoy - a positive, empowering relationship with technology at work - comes from flipping that script.

1. Focus on change management, not just technology

Technology rollouts rarely fail because of the tools themselves; they fail because of poor understanding of the problems they are supposed to solve and of the needs of the people who are destined to use them. The organizations that avoid burnout and disengagement look beyond software selection to the people using it, diving deep into their needs and priorities.

Partnering with experts who understand the human side of digital transformation helps preserve employee autonomy and build supportive cultures where technology empowers rather than overwhelms.

2. Build a supportive, feedback-driven culture that involves employees in decisions

The report revealed that workers prioritize support and empowerment far more than a reduction in the number of tools. When asked what actions their organizations should take to ensure workplace technologies enable rather than frustrate, almost 50% listed ‘a culture where people are comfortable asking for help' as a top-three priority.

Creating that culture starts by involving employees in decision-making, whether selecting tools, designing workflows, or shaping training programs. Understanding their daily challenges before rolling out new solutions and trusting them to decide how best to use technology in their roles builds ownership, in turn, building confidence.

3. Invest in training, support, and resources

Confidence comes through capability. Yet the report reveals that 43% of employees say they need more training, technical support, and access to dedicated learning resources.

Comprehensive onboarding, refresher sessions, and accessible help channels ensure teams don't just use tools but can start to master them by understanding how to best use them in their own personal work context. The key is reinforcing that satisfaction with work isn't about the technology itself but how supported employees feel in using it.

4. Continuously evaluate tools and platforms

Technology and workplace needs evolve constantly and quickly, so should your approach. Regularly assess whether tools are genuinely improving productivity, connection, and well-being, and whether the cumulative effect of using multiple tools is helping or hindering. Ongoing evaluation ensures technology continues to serve its purpose: enabling people to use technology and tools to work smarter, not harder.

Technostress isn't an inevitable side effect of modern work; it's a sign that something in our approach needs to change. The data shows that when people feel supported, well-trained, and understood, technology becomes an enabler, not an obstacle. 

Jon Mort is CTO of The Adaptavist Group

The Latest

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 ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 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.

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 ...

The Path to Technojoy: How to Tackle the Silent Drivers of Technostress

Jon Mort
The Adaptavist Group

Technology's role in the workplace has expanded rapidly, framing how we work and communicate. Now, with the explosion of new and innovative AI-driven tools, people are struggling to navigate how to work in this new emergent era. And although the majority of these applications are designed to make our lives easier, for many knowledge workers, they've become a source of stress and anxiety. "Technostress," a term coined by psychoanalyst Craig Brod in 1984, describes the feelings of being overwhelmed by constant connectivity and cognitive overload from information and notifications, and it's on the rise.

Adaptavist's latest report The human cost of digital transformation, helps paint a more detailed picture. Over the last year, 64% of workers said technology had negatively impacted their lives at work, revealing how deeply embedded technostress has become in our professional lives. Nearly 1 in 3 people pointed to the volume of notifications or the burden of using multiple platforms as key stress drivers.

The sheer scale of this challenge means the consequences extend beyond individual well-being. Technostress is also having a measurable impact on global productivity; Gallup reports that declining employee engagement in 2024 may have cost the global economy as much as $438 billion in lost productivity.

The data suggest that the organizations suffering most are those with poor tool implementation, inadequate training, and weak workplace cultures. So, plotting the path to technojoy (the antidote to technostress) begins with understanding the real needs of your workforce, implementing proper tool training and creating a culture where feedback is not only encouraged but implemented. Organizations that prioritize these elements are seeing their employees embrace technology as an enabler of success, not a burden.

Meanwhile, failure to do so opens businesses up to a workforce increasingly plagued by sickness leave, absenteeism, and high turnover rates.

What's Causing Technostress?

Today's workplaces are defined by digital communication, constant connectivity, and the rise of AI tools. Face-to-face conversations have been replaced by online messages, where tone and intent is harder to read. Employees are juggling meetings and notifications across countless platforms, and are often feeling the pressure to stay connected outside of work hours. One in five workers said messages from colleagues make them feel excluded or incompetent, and a further 28% worried that their tone is easily misinterpreted in online interactions. Together, all these factors create the perfect breeding ground for technostress.

One major driver is insufficient training. With organizations finding their feet as early adopters of these new tools, a fifth of knowledge workers said a lack of guidance on new tools heightens their stress, forcing them to learn through trial and error.

Fueling anxiety and workplace pressure, these demands can be detrimental to employees' mental health and, therefore, workplace relationships and engagement. In fact, a recent study by AI note-taking tool Notta revealed that as many as 42% of workers felt that poor communication affected cross-functional collaboration, suggesting that when tools create friction, it can lead to confusion, anxiety, and a gradual breakdown of team cohesion.

The Symptoms of Technostress

As they play out at work, these shifts are leading to new challenges. Technostress doesn't just affect mental well-being; it can manifest physically, too, with research linking it to headaches, eye strain and a disrupted sleep pattern. Over time, these symptoms can transform into mental fatigue, frustration, and disengagement at work.

The business impact is equally significant. In fact, technostress has become a silent productivity killer, with studies showing employees lose the equivalent of a full working day every month due to dissatisfaction at work, leading to mental disengagement and disempowerment. A blind spot for many leaders is their underestimation of how technology affects employee experience and well-being. Workers feeling overwhelmed by technology are more likely to switch off, underperform, or quietly look for new roles.

These effects are already visible. Around 23% of knowledge workers looked for a new job in the last 12 months, while 12% have taken sick leave or time off work due to technology-related stress. 5% even quit their roles entirely. Given that there are over one billion knowledge workers globally (Gartner), this could translate to 50 million resignations and 120 million job searches each year, an alarming sign of how unchecked technostress could fuel a mass exodus of workers.

What Determines This Impact

The extent to which organizations are affected depends largely on factors like employee happiness, workplace culture, and access to proper training and support. When employees feel supported and energized by their work environment, they report an overwhelmingly positive experience with technology.

60% of workers who said they were supported by a positive workplace culture reported that technology had significantly supported their career advancement and, consequently, improved their satisfaction at work. More than 90% also said that their team integrated technology effectively into collaborative work..

Ultimately, technology alone doesn't solve problems; people do. Without the right structures, digital tools can overwhelm rather than empower. But with the right culture in place, technology becomes what it's meant to be: a catalyst for better work, not the cause of stress and burnout.

Practical Steps Towards Technojoy

If technostress thrives amid poor technology implementation, lack of training, and unsupportive cultures, then technojoy - a positive, empowering relationship with technology at work - comes from flipping that script.

1. Focus on change management, not just technology

Technology rollouts rarely fail because of the tools themselves; they fail because of poor understanding of the problems they are supposed to solve and of the needs of the people who are destined to use them. The organizations that avoid burnout and disengagement look beyond software selection to the people using it, diving deep into their needs and priorities.

Partnering with experts who understand the human side of digital transformation helps preserve employee autonomy and build supportive cultures where technology empowers rather than overwhelms.

2. Build a supportive, feedback-driven culture that involves employees in decisions

The report revealed that workers prioritize support and empowerment far more than a reduction in the number of tools. When asked what actions their organizations should take to ensure workplace technologies enable rather than frustrate, almost 50% listed ‘a culture where people are comfortable asking for help' as a top-three priority.

Creating that culture starts by involving employees in decision-making, whether selecting tools, designing workflows, or shaping training programs. Understanding their daily challenges before rolling out new solutions and trusting them to decide how best to use technology in their roles builds ownership, in turn, building confidence.

3. Invest in training, support, and resources

Confidence comes through capability. Yet the report reveals that 43% of employees say they need more training, technical support, and access to dedicated learning resources.

Comprehensive onboarding, refresher sessions, and accessible help channels ensure teams don't just use tools but can start to master them by understanding how to best use them in their own personal work context. The key is reinforcing that satisfaction with work isn't about the technology itself but how supported employees feel in using it.

4. Continuously evaluate tools and platforms

Technology and workplace needs evolve constantly and quickly, so should your approach. Regularly assess whether tools are genuinely improving productivity, connection, and well-being, and whether the cumulative effect of using multiple tools is helping or hindering. Ongoing evaluation ensures technology continues to serve its purpose: enabling people to use technology and tools to work smarter, not harder.

Technostress isn't an inevitable side effect of modern work; it's a sign that something in our approach needs to change. The data shows that when people feel supported, well-trained, and understood, technology becomes an enabler, not an obstacle. 

Jon Mort is CTO of The Adaptavist Group

The Latest

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 ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 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.

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 ...