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Only 13% of Security Professionals Say User Experience Is Mission-Critical

When employees encounter tech friction or feel frustrated with the tools they are asked to use, they will find a workaround. In fact, one in two office workers admit to using personal devices to log into work networks, with 32% of them revealing their employers are unaware of this practice, according to Securing the Digital Employee Experience, a report from Ivanti.

Yet, just 13% of security professionals say user experience (UX) for end users is a mission-critical priority when adopting cybersecurity tech interventions. By focusing on UX in security measures, organizations can minimize the likelihood of employees bypassing established protocols and resorting to unsafe workarounds.

"Although harmless in the moment, employees typically opt for convenience and put security on the back burner," said Mike Riemer, Field CISO, Ivanti. "Companies should take steps to understand their employees' workplace behaviors and adopt security measures that reduce the temptation for employees to sidestep protocols and use unsafe workarounds. Strong security shouldn't come at the cost of user experience, as it is integral to maintaining both security and productivity."

Key findings from the report include the following:

With the rise of Gen AI, poor security hygiene will increase

When employees have unfettered access to Gen AI tools and other advanced technologies, it can introduce challenges with data privacy, compliance, cyber risks, and copyrighted materials. Ivanti's research shows that 81% of office workers report they have not been trained on Gen AI and 15% are using unsanctioned tools.

Companies aren't providing secure tools for in-office, remote and hybrid work

Whether half of your employees work remotely or just a small fraction do, there is still a profound need to ensure that the company supports all the ways employees work. Only 62% use a VPN or a zero-trust access solution to restrict network access and protect sensitive information, and only 57% use multi-factor authentication.

Security leaders are often excluded from DEX investment decisions

Digital employee experience (DEX)-informed security minimizes the need for employees to change their typical behaviors at work. Yet, only 38% of companies consult the CISO for input on DEX strategy, investments, and planning, despite the significant contributions DEX tools can make to security.

Methodology: Ivanti surveyed over 20,000 IT professionals, executive leaders, office workers and security professionals around the world to understand what organizations are doing to enable positive digital employee experience (DEX) and any barriers organizations face to deliver frictionless experiences.

The Latest

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Only 13% of Security Professionals Say User Experience Is Mission-Critical

When employees encounter tech friction or feel frustrated with the tools they are asked to use, they will find a workaround. In fact, one in two office workers admit to using personal devices to log into work networks, with 32% of them revealing their employers are unaware of this practice, according to Securing the Digital Employee Experience, a report from Ivanti.

Yet, just 13% of security professionals say user experience (UX) for end users is a mission-critical priority when adopting cybersecurity tech interventions. By focusing on UX in security measures, organizations can minimize the likelihood of employees bypassing established protocols and resorting to unsafe workarounds.

"Although harmless in the moment, employees typically opt for convenience and put security on the back burner," said Mike Riemer, Field CISO, Ivanti. "Companies should take steps to understand their employees' workplace behaviors and adopt security measures that reduce the temptation for employees to sidestep protocols and use unsafe workarounds. Strong security shouldn't come at the cost of user experience, as it is integral to maintaining both security and productivity."

Key findings from the report include the following:

With the rise of Gen AI, poor security hygiene will increase

When employees have unfettered access to Gen AI tools and other advanced technologies, it can introduce challenges with data privacy, compliance, cyber risks, and copyrighted materials. Ivanti's research shows that 81% of office workers report they have not been trained on Gen AI and 15% are using unsanctioned tools.

Companies aren't providing secure tools for in-office, remote and hybrid work

Whether half of your employees work remotely or just a small fraction do, there is still a profound need to ensure that the company supports all the ways employees work. Only 62% use a VPN or a zero-trust access solution to restrict network access and protect sensitive information, and only 57% use multi-factor authentication.

Security leaders are often excluded from DEX investment decisions

Digital employee experience (DEX)-informed security minimizes the need for employees to change their typical behaviors at work. Yet, only 38% of companies consult the CISO for input on DEX strategy, investments, and planning, despite the significant contributions DEX tools can make to security.

Methodology: Ivanti surveyed over 20,000 IT professionals, executive leaders, office workers and security professionals around the world to understand what organizations are doing to enable positive digital employee experience (DEX) and any barriers organizations face to deliver frictionless experiences.

The Latest

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...