Enterprise mobility is no longer about issuing better smartphones. From silicon and connectivity to AI-driven management and specialised peripherals, the entire mobile stack is evolving—unlocking new workflows for frontline, hybrid and globally distributed teams.
For years, enterprise mobility strategies revolved around device refresh cycles. Faster processors, better cameras and longer battery life were considered the markers of progress. But today, the handset is just one layer in a far more complex ecosystem.
Across industries, larger organisations are discovering that the real transformation lies beneath the surface. Silicon innovation, resilient connectivity, edge intelligence, device experience platforms and specialised accessories are converging to create a new “mobile stack”—one that determines whether frontline and hybrid teams can operate efficiently, securely and autonomously.
According to IDC, global spending on enterprise mobility solutions is expected to surpass $700 billion in 2026 (IDC). Meanwhile, Gartner predicts that by 2027, over 50% of enterprise data will be created and processed outside traditional data centres or cloud environments. The shift is unmistakable: mobility has become distributed, intelligent and deeply integrated into operational workflows.
Performance and Connectivity Redefine the Centre of Gravity
If the smartphone is no longer the centre of enterprise mobility, what is?
Steven Vindevogel, Head of Panasonic TOUGHBOOK Europe, says performance has become the defining layer. “We are betting on performance becoming the most critical element for enterprise mobility,” he says.
Earlier waves of mobility prioritised portability and cost, driven by Android and iOS adoption and cloud-based applications. But AI-enabled workloads and improving 5G infrastructure are reshaping expectations. “Better connectivity and access to more real-time data can drive workforce efficiencies. However, to really take advantage, many businesses are preferring to invest into high performance platforms that will future proof their deployments,” he says.
Connectivity, however, is equally pivotal. Kristian Torode, director and co-founder of connectivity expert Crystaline, says the network layer has become the most critical—and most overlooked—part of the stack.
“While smartphones remain essential, connectivity has become the most critical layer of the mobile stack,” Torode says. He explains that organisations often assume new handsets will solve productivity issues, when unreliable networks and poor upload speeds are the real constraint.
In practice, connectivity remains a friction point. Although 5G promises low latency and high throughput, many regions are still transitioning to fully standalone 5G networks. For service-oriented organisations moving line-of-business applications into the cloud, inconsistent connectivity introduces operational risk.
At the same time, new network architectures are enabling entirely new workflows. Torode says technologies such as 5G, and private LTE now support real-time machine monitoring and the synchronisation of hundreds of endpoints simultaneously. For distributed teams, that means the difference between reactive operations and coordinated, data-driven execution.
Edge Intelligence Changes Frontline Reality
Perhaps the most profound shift is occurring at the silicon layer.
Advances in Neural Processing Units (NPUs) and energy-efficient system-on-chips are pushing AI processing onto the device itself. Vindevogel says this is turning previously “dumb” devices into autonomous tools capable of operating without constant connectivity.
In frontline environments—mines, farms, disaster zones or factory floors—this has tangible consequences. Devices can maintain AI capabilities such as voice commands and predictive assistance even in signal “dead zones,” eliminating functional blackouts. Edge AI cameras can detect safety risks in real time. Wearables can monitor fatigue or hazardous exposure and trigger immediate interventions.
Instead of halting work when the signal drops, teams can continue operating with on-device intelligence. Privacy also improves, as sensitive data can be processed locally rather than transmitted externally. Routine administrative tasks such as filing reports or tracking inventory can be automated by AI, freeing staff to focus on higher-value activities.
Torode agrees that advances in silicon are expanding what can be done at the edge. Dedicated AI chips now allow complex analytics and workflow automation directly on devices in warehousing and manufacturing environments. Tasks that once depended on cloud connectivity—such as sensor monitoring and reporting—can now be executed locally.
For enterprises, this changes the return-on-investment equation. Investment in edge-capable devices is no longer about incremental performance gains; it is about enabling autonomous operations, reducing downtime and strengthening data governance.
Managing Complexity Across Distributed Fleets
As capabilities expand, so too does complexity. Larger organisations must balance platform standardisation with the need for role-specific devices and form factors.
Vindevogel acknowledges the tension. Standardisation reduces support costs, training requirements and spare parts complexity—particularly when teams are geographically dispersed. But AI-optimised workflows may demand differentiated hardware to unlock productivity gains.
Torode recommends a hybrid approach. Standardise core operating systems and management platforms, he says, while allowing flexibility for rugged devices and wearables where they deliver measurable productivity improvements.
Endpoint management has therefore become the connective tissue of the mobile stack.
Vindevogel says it is now possible to collect extensive data from endpoint devices and turn those insights into proactive action. Businesses can monitor connectivity and battery performance across entire fleets following application updates, ensuring user experience is not compromised.
Torode comments that AI-driven automation for device provisioning and predictive maintenance—capabilities that were fragmented or unrealistic only a few years ago—are now embedded in modern platforms. Centralised dashboards allow IT teams to manage hybrid workforces and IoT endpoints at scale.
Yet the barriers to realising full value are often organisational rather than technical. Torode says inconsistent connectivity and siloed endpoint management remain persistent obstacles. Vindevogel adds that legacy applications and equipment integrations frequently limit organisations’ ability to adopt new technologies at pace.
Mobility treated as a device procurement exercise will inevitably underdeliver. Mobility treated as an architectural strategy can unlock compounding efficiencies across the enterprise.
The Disproportionate Power of Peripherals and the Rise of Agentic AI
In many cases, the most transformative investments are not in the core device at all.
“Ultimately, the peripherals and accessories really define the solution,” Vindevogel says. Scanners, rugged add-ons and wearables often complete a use case and create outsized value compared to upgrading the handset alone.
Torode echoes this view. Accessories such as barcode scanners can dramatically improve efficiency in logistics and warehousing. In many cases, a carefully selected peripheral enables a workflow that replaces multiple manual processes, delivering greater return than incremental handset improvements.
Looking ahead, both experts point to emerging layers of the stack that could prove disruptive.
Vindevogel highlights the opportunity of a “Wireless-First” future powered by private 5G and edge computing. This will be critical for the low-latency processing required by mobile AI agents and real-time operational models in sectors such as manufacturing and field service. He also anticipates Agentic AI becoming highly disruptive within mobile IT environments, as organisations prioritise Mobile Digital Employee Experience and proactive monitoring software that tracks device telemetry and user sentiment in real time.
In this environment, success will increasingly be measured by downtime avoided and incidents resolved automatically—rather than simple device uptime.
Torode says edge intelligence and AI-driven analytics at the device level are poised to reshape enterprise mobility strategies. Leaders, he advises, should prepare by investing in robust connectivity and unified management platforms that integrate cloud and IoT workflows.
For enterprise decision-makers, the conclusion is clear. The mobile stack is no longer a peripheral IT concern. It is a strategic enabler of workforce capability, operational resilience and competitive advantage.
The question is no longer which handset to buy next. It is whether the organisation has architected its mobility ecosystem—silicon, connectivity, management, peripherals and AI—to support the workflows of tomorrow.
