Enterprise mobility 2026: GenAI and autonomy take center stage

One of the most important trends in unified endpoint management (UEM) and mobility management is — surprise! — a big move toward AI-enabled capabilities. But this is only part of what is a quickly evolving market.

“The endpoint management market is undergoing a rapid transformation fueled by SaaS-powered innovations, deeper integration of threat intelligence, growing reliance on digital [employee] experience tools, and breakthroughs in AI/ML and generative AI [genAI],” says Tom Cipolla, vice president and analyst, Digital Workplace Infrastructure and Operations at research firm Gartner.

“These trends are setting the stage for next-generation solutions that prioritize automation and intelligence,” Cipolla says.

AI, and specifically genAI, are now solidly part of the mobility landscape, as enterprises and vendors continue to look for ways to automate functions and increase efficiency.

The AI push

Many current platforms include genAI capabilities designed to make the platforms easier to use through conversational interfaces, Cipolla says. “AI is starting to be used to analyze data and make recommendations for device management efficiency,” he says.

Natural language assistants and chatbots, patch management and predictive maintenance, AI-driven security and threat detection, and insight generation and reporting are four major areas where genAI is accelerating operations and reducing labor, Cipolla says. Wider-scale usage of genAI will depend on vendors releasing capabilities that allow administrators to chat with their data and uncover insights not previously available via existing dashboards and reports, he adds.

One AI technology that has yet to take off in UEM is agentic AI, Cipolla says. This involves the use of AI applications known as agents that execute complex workflows, make decisions, take actions, and interact with other agents — all with limited oversight from humans.

“Agentic AI is a potential transformational force in endpoint management tools, but not currently widely enabled by vendors,” Cipolla says. “We are watching this closely as we expect rapid innovation. Agentic AI not only can generate insights, but can act based on those insights and the risk, business, and operational goals of the organization.”

The complexity of modern endpoints and the reliance on devices for more tasks and use cases can leave workers under-provisioned in terms of the software and configurations required to do their jobs at a basic level, says Phil Hochmuth, research vice president, Endpoint Management and Enterprise Mobility at research firm IDC.

“The emergence of AI can help organizations take a large step forward toward hyper-customizing end-user devices for exactly the job they do — from optimizing the installed software to ensuring the right levels of connectivity, access control, and data access privileges are enabled when users unbox their PCs or laptops,” Hochmuth says.

While automated patching, deployment, and alerting have been around for some time, “now we’re seeing vendors lean more heavily into AI,” says Jeremy Roberts, senior director, research and content at Info-Tech Research Group. “I think there is significant overlap with AIOps [AI for IT operations] to facilitate automation across the entire stack, and these tools require input of the sort collected by traditional UEM tools.”

Predictive analytics is the biggest use case for AI in UEM, Roberts says, to address questions such as “when is a device likely to die, [or] what is likely causing a poor experience?” Managers are focused on productivity, “and preemptively remediating issues before they cause productivity problems is definitely an area for UEM to shine,” he says.

Enterprises need to understand their genAI use cases well and make a case for return on investment, Roberts says. “AI is not good for its own sake,” he says. “Look for things that AI is good at: anomaly detection, predictive analytics are cool.”

As with other applications of AI and automation, the technology should not just replace people, but enable them to be more productive. “Keep humans in the loop until you’ve figured out how the system behaves with confidence,” Roberts says. “It’s not a given that AI will make things easier or more efficient, so keeping an eye on the system before you let auto-remediation run rampant is wise.”

A related trend is the growing use of autonomous endpoint management (AEM), an approach that uses AI and machine learning to automate device management for greater efficiency, security, and compliance. AEM handles tasks such as patching and configuration.

“Demand for autonomous actions will surge within the next three years, as IT leaders and managed service providers struggle to scale staffing and skill sets to meet operational demands,” Gartner’s Cipolla says. “In response, vendors are embedding [AEM] into their offerings.”

While current implementations focus on intelligence-driven patch automation, Cipolla says, Gartner predicts AEM will soon expand to include configuration and policy management, among other critical workloads.

Stable market

The endpoint management market continues to be highly mature, dominated by a handful of vendors with significant market share, Cipolla says. Despite this concentration, Gartner notes that many organizations supplement their primary UEM platform with competitive or complementary tools to close gaps or enhance underperforming capabilities.

“As a result, Gartner has reformatted the market to include the broader endpoint management tool vendors,” Cipolla says. “Gartner projects moderate topline growth over the next several years, as mainstream modern-management-based UEM solutions work to bridge functionality gaps compared to traditional client-based tools,” he says.

These gaps — often related to speed, reliability, and granularity — create operational overhead and remain key barriers to efficiency in endpoint operations, Cipolla says.

In response to a need to move faster to patch devices and reduce security risks, many endpoint management platforms have started to provide real-time measurements of digital employee experience (DEX) into their platforms, Cipolla says.

“This data is used to very quickly determine whether [an] impact is seen, and the platform can halt operations if negative signals are received and also accelerate operations if positive signals are seen,” Cipolla says. “This is referred to as operational digital employee experience measurements, or OpDEX. OpDEX is at the heart of the autonomous endpoint management approach.”

A key mobility management dynamic involves balancing the ideal of a single unified platform with the practical needs of managing advanced use cases and functions, according to IDC’s Hochmuth.

“Enterprises report that full convergence is often stymied by the diversity of use cases — frontline workers, field staff, knowledge employees, and device fleets operating on a mix of Windows, Mac, iOS, Android, Chromebooks, and specialized IoT [Internet of Things] or single-purpose devices,” he says. “As a result, many organizations adopt multi-vendor UEM deployments, choosing specific tools based on best-fit features for distinct operational or regulatory demands.”

As for the cost of UEM platforms, there has not been an increase in UEM pricing over the past year, in terms of price per device or user per month, Hochmuth says. “However, premiums will be charged for AI-based and automation-based intelligence ‘add-on’ products to UEM suites,” he says.

Looking ahead, predictive analytics will become a standard, baseline function of endpoint device management tools, Hochmuth says. “AI will augment this function to help IT teams preempt endpoint device failures, optimize resource allocation, and improve device uptime based on usage patterns and telemetry,” he says.

As IT operations moves toward a future of smaller IT teams, “organizations will have to rely on help from data-driven AI and automation capabilities to manage ever-growing fleets of endpoints, from mobile devices and PCs, and beyond,” Hochmuth says.

Related:

GenAI is coming to your UEM platform: How to prepare

UEM buyer’s guide: How to choose the right unified endpoint management platform

What is UEM? Unified endpoint management explained

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