For years, enterprise IT has been caught in a familiar cycle. Something breaks, a ticket is created, a technician investigates, and eventually the issue is resolved. The tools have improved, the visibility is sharper, and response times are faster. But the underlying model has remained largely unchanged. IT reacts.
What has changed is the scale of the problem. Endpoints now span physical devices, virtual desktops, SaaS applications, and multiple cloud environments. Hybrid work has dissolved the boundaries of the traditional network. Each new layer introduces more signals, more variability, and more opportunities for failure. The result is not just complexity, but a growing gap between what IT can see and what it can realistically manage.
Visibility was the first step, not the solution
The industry has already invested heavily in closing the visibility gap. Digital Employee Experience platforms made it possible to understand how technology performs from the user’s perspective in real time. That was a meaningful step forward. It revealed friction that had previously gone unnoticed and gave IT a clearer view of its impact on productivity.
But visibility created its own problem. The more insight IT gained, the more it had to act on. Seeing issues faster did not mean resolving them faster. In many environments, the bottleneck simply moved downstream. While detection capabilities have advanced, resolution efficiency has failed to keep up.
This is the point where a new model begins to emerge. The goal is no longer just to identify issues quickly. It is to resolve them automatically and, increasingly, to prevent them from happening at all. This shift aligns with emerging industry direction from Gartner around Digital Workplace Operations and Automation (DWOA) platforms, which emphasizes proactive, automated and experience-centric IT operations.
From insight to action
A new approach is taking shape that connects telemetry, intelligence, and action into a continuous system. Endpoints generate real-time data about performance, configuration, and user experience. AI analyzes that data to identify anomalies and determine likely root causes. Automation then executes remediation without waiting for human intervention.
The process is not a simple workflow. It is continuous and adaptive. Systems learn from patterns, adjust to changing conditions, and act in real time.
This is where artificial intelligence (AI) moves beyond assistance and into true decision-making. Traditional automation relies on predefined rules and predictable conditions, which limits its effectiveness in today’s highly dynamic environments. Agentic AI changes that by introducing contextual awareness, enabling systems to interpret multiple signals simultaneously and determine the most appropriate course of action in real time.
The impact is already becoming clear. Gartner® predicts “By 2030 AI assistants, AI agents and AI-powered automation will result in at least a 75% reduction in digital workplace tickets requiring human intervention. Early successes include 87% faster patching with minimal impact on DEX caused by disruptions.1”
Early capabilities are also delivering measurable operational gains, including reductions in patch cycle times of up to 87 percent.1
The barrier is not technology, it is mindset
Despite the progress, adoption is not moving as quickly as the technology itself. Many organizations are still applying AI to low-risk, low-value use cases. Cultural inertia plays a significant role. IT teams have long operated in environments where stability and control are paramount, and that has created a natural reluctance to trust autonomous systems.
That hesitation is becoming harder to justify. Organizations that fail to evolve toward more autonomous operations risk falling behind in both efficiency and cost. Gartner further predicts “By 2029, over 50% of heads of I&O who fail to enable autonomous operations will be replaced due to inefficiencies, errors, and higher costs.1”
The challenge is no longer whether the technology works. It is whether organizations are willing to change how they operate.
IT moves from fixing to enabling
As systems take on more operational work, the role of IT begins to shift. Less time is spent resolving repetitive incidents. More time is spent shaping the environment, defining policies, and improving outcomes.
This shift is already influencing how organizations think about talent. Technical expertise remains essential, but it is no longer the only differentiator. As routine tasks are automated, skills like adaptability, communication, and empathy become more important. More than a third of organizations are expected to prioritize these qualities in digital workplace roles in the coming years.
At the same time, the boundaries between IT and the business are becoming less defined. Delivering a seamless digital experience requires collaboration across functions, particularly with HR and business teams. Organizations that embrace this multidisciplinary approach are significantly more likely to achieve positive outcomes.
A shift from tools to outcomes
For years, digital workplace strategy was driven by tools. New platforms, new dashboards, and new layers of visibility defined progress. That model is giving way to something more outcome-focused.
What matters now is not how much data IT can collect, but what it can do with it. Reduced disruption, improved productivity, and stronger employee experience are becoming the primary measures of success. This outcome-driven model is also central to emerging DWOA strategies, which unify monitoring, analytics and automation into a single operational discipline focused on employee experience and business impact.
This is where Autonomous Endpoint Management (AEM) enters the conversation. It represents the convergence of visibility, AI-driven intelligence, and automated action into a single operating model. It closes the gap between knowing and doing. As recent Gartner research2 states “The rise of AI agents will significantly increase the potential for many IT functions to happen without human intervention, but it will be a challenge for both vendors and IT organizations to increase their autonomous capabilities or tools.2”
When problems disappear before they are seen
Endpoints are no longer just devices to manage. They are the primary interface between employees and the business. Every delay or disruption has a direct impact on productivity and perception.
By continuously monitoring, analyzing, and optimizing performance, intelligent systems are beginning to change that experience. Issues are detected earlier. Root causes are identified faster. Remediation happens automatically.
In many cases, the user never notices anything went wrong. That is the real promise of this shift. Not faster response times, but fewer visible problems altogether. This is the foundation of AEM, where AI-driven systems increasingly operate independently to maintain device health, enforce policies, and optimize performance without human intervention.
“By 2029, over 50% of organizations will adopt AEM capabilities within advanced endpoint management and DEX tools, an increase from 15% in 2026.1”
As that happens, expectations will change. Technology will be judged less by how quickly it can be fixed and more by how rarely it fails in the first place.
For IT teams that have spent years reacting, it marks a fundamental shift in how their role is defined.
1,3 Gartner, Inc., “Predicts 2026: AI Will Shift Digital Workplace Focus From Tools to AI-Augmented People,” Robin Milton-Schonemann, Autumn Stanish, Stuart Downes, Todd Larivee, Tom Cipolla, Hanne Nieberg, LJ Justice, Tori Paulman, Erin Pierre, December 24, 2025 . Gartner is a trademark of Gartner, Inc. and/or its affiliates
2 Gartner, Inc., “The Impact of AI Agents on Digital Workplace IT Operations,” Stuart Downes, Autumn Stanish, September 16, 2025
About the Author
Simon Townsend is a prominent end user computing technology evangelist, marketer and thought leader. As Senior Vice President of Marketing and Head of the Office of the CTO, he leads the company’s marketing strategy and team of digital, field, channel and product marketers and technical experts, worldwide. He joins ControlUp from IGEL where he served as Field CTO for EMEA and Chief Marketing Officer, overseeing field, digital and product marketing functions. With more than 20 years of experience in the end-user computing market, Townsend has held leadership positions in marketing, product marketing, product management and global systems engineering for several enterprise software companies including Ivanti, AppSense, Servo and Westcon UK.
