Skip to main content

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 Face-to-face conversations have been replaced by online messages, where tone and intent is harder to read.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

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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

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 ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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

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 ...