AI-driven Proactive Care: Redefining
Device and Service Management at Scale
Whether issues arise at home or while moving between cells, they expect operators to manage their service with the same predictability. dependability, and coherence at any touchpoint, any device, any service.
The new standard is an experience where problems are anticipated and removed before they surface, and correspondingly, the edge environment performs as reliably as the core.
Device and service management
is now a CX function
When the customer experience is defined by what happens on the device and across the customer’s digital journey, deep visibility and control at the device and service access layers become
frontline CX capabilities. This now converges both fixed and mobile environments, where experience is shaped not only by WiFi, mesh, and in-home conditions, but also by radio behavior, cell and
RAT handovers, roaming policies, and device-specific performance under load, all of which can degrade service even when the core network is performing as expected.
To resolve issues proactively, operators must have visibility in full context: the particular device, running which firmware version, in which environment, at what time, using which application,
and so on. For mobile users, they also need to be aware of whether voice, data, or messaging entitlements (e.g. VoLTE/VoNR, RCS, 5G Slicing) are properly activated; whether eSIM/iSIM provisioning
has completed; and whether APN and/or IMS settings are correctly applied. These areas are frequent sources of customer-perceived “network problems” and are core to modern device and service
orchestration workflows.
But visibility alone is not enough. Operators must also be able to act within that same context, reconfiguring radios, updating profiles, nudging the right self-care actions, triggering
entitlement repair flows, or orchestrating a multisystem-fix automatically without the customer ever needing to intervene.
Customers don’t perceive their service in domains; they experience it as a single continuum. Whether issues arise at home or while moving between cells, they expect operators to manage their
service with the same predictability. dependability, and coherence at any touchpoint, any device, any service.
This makes everyday edge environments, both fixed and mobile, the decisive battleground for satisfaction and loyalty. Most issues that undermine trust originate here: interference, mesh
instability, weak handover behavior, misprovisioned subscription profiles, or inconsistent application performance.
These problems may be invisible to traditional network-centric tools, but they are immediately noticeable to customers. When the experience fails at the edge, the customer relationship
weakens.
The shift to AI‑driven proactive care
Protecting that relationship requires a new model in which device intelligence, edge visibility, and entitlement-aware service management are not peripheral activities, but core pillars of the customer experience. This is why operators are increasingly shifting toward AI-driven predictive and proactive care.
Instead of seeing service performance as a backlog of incidents waiting to be handled, AI reframes it as a continuously evolving signal loop that can be monitored, interpreted, and acted on in
near real time.
In mature service operations, proactive care represents the highest stage of evolution: operators identify and resolve issues before customers even become aware of them. Rather than waiting for a
customer to recognize a problem and seek help, AI-powered automation anticipates impending service degradation and initiates corrective actions automatically and safely.
This shift is enabled by a connected loop operating model, where AI continuously senses anomalies, detects root causes, decides the appropriate action, and learns from each outcome to improve
future responses. This ecosystem of involvement shortens time to resolution and increasingly prevents incidents from affecting customers at all.
