VMware is announcing four unique enhancements to further its comprehensive DEX solution: the general availability of DEX for 3rd party managed devices, DEX for VMware Horizon, AI-driven Guided RCA, as well as the intent to expand Workspace ONE ITSM Connector for ServiceNow support of available remediation actions.
These innovations combine to advance VMware’s commitment to deliver the only holistic DEX solution, which helps to increase productivity and provide faster issue remediation, enabling higher employee engagement.
“Organizations across industries are struggling to keep up with the increased IT incidents and growing employee turnover rates as they navigate the new challenges brought on by hybrid work. Successful organizations must prioritize technology that enables IT teams with the right tools to not only resolve issues faster, but prevent them from happening in the future,” said Shankar Iyer, SVP and GM, End-User Computing, VMware. “VMware’s comprehensive DEX solution uses automation to enable IT teams with data-driven insights that enable improved efficiency and great experiences for employees.”
VMware progresses its DEX solution by unifying employee experience measurement across all endpoints, whether physical or virtual and VMware or 3rd party managed. VMware announced that its Digital Employee Experience Management (DEEM) solution is now generally available for Windows devices managed by 3rd party solutions. With this update, VMware’s entire DEX offering, including Intelligent Hub, DEEM, and Assist, is now available for these devices. Even if a customer has standardized on other management solutions, this capability provides customers with more flexibility in how they deploy and grow their DEX solution.
For customers ready to extend measurement to virtual apps and desktops, VMware announced that DEEM is also generally available for VMware Horizon. Customers can measure and analyze end-user experiences using Horizon virtual apps and desktops, bringing together network performance, log on time, and VM performance. If the experience score for Horizon changes, IT will be proactively alerted with automated notifications, enabling teams to more efficiently resolve issues impacting employee productivity using the Horizon platform for work.
Organizations cannot achieve a seamless employee experience without also controlling experience delivery and issues remediation. VMware a solution that creates a closed loop cycle that allows IT to shift left, leveraging holistic experience data to proactively resolve issues and continuously improve employee experiences. With the VMware Workspace ONE award-winning unified endpoint management capabilities, customers have access to the broadest scope of remediation capabilities available today.
By extending the same experience data that IT views in Workspace ONE into ServiceNow via VMware’s ITSM Connector, service desk teams can troubleshoot and resolve issues more efficiently. VMware unveils further innovations to ITSM Connector including experience scoring, an expanded set of unified endpoint management actions, and the ability to trigger workflows created by IT teams in VMware Freestyle Orchestrator. By leveraging experience scores, the service desk can proactively resolve other potential issues impacting a user before it escalates and hinders workflow. These expanded remediation actions and workflows will continue to help decrease the time required to troubleshoot and resolve each issue.
VMware’s DEX offerings empower IT through Insights, Guided Root Cause Analysis (RCA), and Automation, enabling a proactive approach to IT. With AI-driven insights, IT organizations have immediate visibility into issues that are impacting employee productivity by using statistical machine learning models to automatically detect and score anomalies in experience. Guided RCA, now generally available, uses AI to identify the likely root cause of an issue with an associated confidence score. This helps reduce the time and effort required to identify the problem source. With integrated automation workflows, the appropriate remediation actions can be taken moving forward, scaling issue resolution and proactive employee notification.
The Latest
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 ...
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.