Organizations have invested heavily in observability platforms, yet a quiet crisis is undermining every dashboard, and every digital experience initiative: too many endpoints remain unmanaged, and under-instrumented.
Unified Endpoint Management (UEM) is not a peripheral Information Technology (IT) concern; it is the foundation that determines whether observability produces real intelligence or expensive noise. Without comprehensive endpoint coverage, even the most sophisticated monitoring architecture is answering the wrong question.
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The observability imperative has reached the edge
The pressure to deliver always-on, frictionless digital experiences has pushed observability from a niche concern to a board-level priority. The ability to understand the internal state of a system based on the data it generates has become strategically critical. Increasingly, that system extends all the way to the employee’s laptop, mobile devices, Internet of Things (IoT) sensors, and smart peripherals.
This endpoint data proliferation is also driving growth in the overall enterprise mobility and UEM services market. Everest Group estimates the global UEM outsourced services market at US$11-13 billion, with expected growth of 10-12% CAGR over the next three years. Yet strong services growth also highlights a deeper problem: deploying a UEM tool is not the same as operationalizing endpoint intelligence. The gap between enrollment and insight remains wide, and that gap prevents unified observability from becoming reality.
Deploying a UEM platform is not the same as operationalizing endpoint intelligence. The gap between enrollment and insight remains wide.
Two structural challenges blocking unified observability
Exhibit 1 highlights the two core challenges enterprises face in modern device management: fragmented visibility across diverse device ecosystems and persistent blind spots created by unmanaged endpoints.
Challenge 1: data fragmentation and the visibility debt
Modern enterprises operate across a heterogeneous landscape, including Windows and macOS desktops, iOS and Android mobile devices, smart eyewear, drones, humanoids, Point-of-Sale (PoS) machines, Linux servers, rugged field devices, and an expanding frontier of IoT and operational technology. Each category generates its own telemetry, is managed by its own toolset, and often reports into its own silo.
This fragmentation creates what analysts call visibility debt: the accumulating cost of not knowing what you do not know about your endpoint estate.
Platforms such as Microsoft Intune have made significant strides in aggregating Windows and mobile device telemetry into a unified console, and Jamf has deepened native Apple ecosystem intelligence, making it the preferred UEM layer for macOS- and iOS-centric organizations. ManageEngine’s Endpoint Central offers cross-platform breadth across Windows, macOS, Linux, iOS, Android, and Chrome OS, particularly valued by mid-market enterprises seeking cost-effective coverage. However, even best-in-class tools face an architectural reality: no single provider controls every device and operating system category in every enterprise.
Data fragmentation is therefore not a product failure but a structural inevitability that only a deliberate integration strategy can address.
Challenge 2: incomplete endpoint coverage and observability’s blind spots
The second structural challenge is more fundamental: enterprises cannot observe what they do not manage. Observability platforms, whether built on OpenTelemetry standards championed by the Cloud Native Computing Foundation (CNCF) and the Linux Foundation or delivered by Artificial Intelligence (AI) for IT operations (AIOps) providers, are increasingly sophisticated at synthesizing infrastructure, application, and network signals. Their ceiling, however, is the completeness of the endpoint data they receive. When a device is unmanaged, it is effectively invisible; incomplete coverage does not merely create a security gap, it creates an intelligence gap.
Ivanti Neurons represents one direction the market is moving, using AI-powered discovery to continuously identify unmanaged endpoints and pull them into managed scope. Hexnode has carved out a compelling niche in kiosk and purpose-built device management, addressing IoT and frontline worker endpoints that traditional UEM tools frequently overlook.
These approaches reflect the same underlying conviction: the path to observability runs through the endpoint, and every unmanaged device is a gap in the enterprise intelligence fabric.
Why endpoint management must come first
The temptation for enterprise technology leaders is to invest in observability platforms first and then address endpoint coverage incrementally. That sequence is flawed.
Consider a global supply chain. Even the most advanced control tower is only as effective as the completeness of the data it receives. If inventory, shipment status, or demand signals are missing from a few critical locations, the entire system’s view becomes distorted. Decisions made on incomplete data can lead to stockouts, overstocking, or delayed deliveries, not because the analytics are weak, but because the inputs are incomplete.
Observability works the same way. An AIOps platform ingesting telemetry from only 60% of endpoints will generate insights optimized for a partial and unrepresentative view of the environment. The result is false confidence, where systems appear healthy on dashboards, while underlying issues remain undetected.
Once endpoints are comprehensively managed, the incremental value of each observability capability, including performance baselining, anomaly detection, and predictive remediation, increases nonlinearly. A UEM platform managing 95% of endpoints does not simply deliver 95% of potential observability value. It delivers substantially more because correlation quality improves with coverage.
From device management to holistic experience-centric observability
The UEM providers that define the next decade will recognize the evolution of their mandate. Device management, covering patching, compliance, and configuration, remains essential, but is no longer sufficient. The new competitive frontier is holistic, experience-centric observability: the ability to not just manage endpoints but to use endpoint data to understand, predict, and improve the quality of human experiences behind those devices.
This experience is no longer limited to knowledge workers operating laptops and mobile devices. It extends to frontline workers using rugged devices, clinicians relying on specialized endpoints, retail associates using PoS systems, and even automated endpoints embedded in operational environments. Delivering meaningful insights, therefore, requires visibility across all endpoint types, not just traditional IT-managed devices.
This shift is already underway. Digital Employee Experience (DEX) scores, which measure application performance, device health, connectivity quality, and user sentiment, are becoming standard reporting artifacts for Chief Information Officers (CIOs). Microsoft Intune, integrated with Windows Autopilot and Microsoft 365 telemetry, is well positioned to correlate device-level signals with productivity application performance. Jamf Pro and Jamf Connect deliver comparable depth for Apple-centric organizations, with a growing focus on employee experience metrics tied to enrollment health and application delivery performance.
Meanwhile, ManageEngine’s integration with the Zoho ecosystem creates an opportunity for cross-functional experience intelligence that spans IT operations and business productivity data. Ivanti continues to lead on the automation frontier, with Neurons using machine learning to move from reactive device management to predictive remediation.
The opportunity, and the obligation, for UEM providers is to evolve from systems of record to systems of insight for human experience. This evolution requires machine learning models that can distinguish between network and device issues, behavioral changes and compliance risks, and isolated incidents versus systemic experience failures, across all users and endpoint types.
Final thoughts: strengthen the foundation before chasing the penthouse view
Unified observability is not a product enterprises deploy. It is a capability they earn, layer by layer, starting from the edge. Without a strong foundation, data remains partial, insights remain skewed, and experience improvements remain aspirational. Exhibit 2 depicts the clear strategic progression.
UEM is not the last mile of an observability strategy. It is the first. Additionally, with the growing impact of UEM, Everest Group is launching the Unified Endpoint Management (UEM) Top 50 – 2026 report. The report will assess leading UEM technology providers based on their scale, capabilities, and market relevance, including how they are enhancing their offerings across automation, analytics, endpoint intelligence, and DEX. It will also examine the challenges and opportunities shaping the next phase of UEM evolution.
If you are interested in learning more about the assessment process or wish to participate, please provide your details using the form below and we will reach out to you: Everest Group Top 50™ Unified Endpoint Management (UEM) Technology Providers 2026
To discuss how your organization can redefine its UEM platform value proposition, reach out to Prabhneet Kaur ([email protected]_), Aman Bhargav ([email protected]), or Hemant Singh ([email protected]).