Networks for the AI Era | Free White Paper

Free Insights White Papers June 9, 2026

Learn How Connectivity Infrastructure Must Evolve to Meet Enterprise Demands

IoT connectivity is seeing a dramatic shift. Price is no longer the leading factor for many customers, as connectivity is now a compliance concern. Cross-border data regulatory restrictions and a growing need for data sovereignty among enterprises due to AI deployment are driving the new era of connectivity. How data is handled and supports the enterprise outcome is now a fundamental consideration.

What the Report Covers

Regulatory fragmentation now drives architectural decisions: Compliance has moved well beyond personal data (GDPR) to include non-PII and critical infrastructure data. Countries are enforcing strict localisation rules (e.g., EU Data Act, France’s SecNumCloud, UK Telecom Security Act, Australia’s SOCI Act), while AI regulation (EU AI Act, China’s Interim Measures for the Management of Generative Artificial Intelligence Services) adds further complexity. Connectivity providers must design networks that keep payload and signalling traffic within national borders to avoid regulatory breaches.
AI is fundamentally altering IoT traffic asymmetry: Enterprise AI workloads disrupt traditional uplink/downlink ratios. Cloud-based inference can increase uplink traffic by up to 700%, while on-device or edge models require substantial downlink capacity for frequent model updates (ranging from hundreds of MBs to several GBs). Networks must be dimensioned and routed to handle these highly asymmetric, real-time data flows without degradation.
Latency, jitter, and availability are now mission-critical: As IoT shifts from passive telemetry to autonomous, actuation-driven systems, network performance directly impacts application safety and compliance. Monolithic hardware gateways struggle with deterministic latency and graceful failover; cloud-native, stateless core architectures are required to maintain continuous data streams and minimise session disruption during node failures.
Edge-centric infrastructure and direct interconnects are mandatory: Legacy regional packet gateway models can no longer meet sovereignty or performance demands. Providers must deploy virtualised, software-defined gateways in-country or at metro level, establishing direct interconnects to edge sites and sovereign clouds. Proximity to inference workloads is essential to minimise the ‘last mile’ transport path and support low-latency operations.
Observability and programmable security are non-negotiable: Security must evolve beyond perimeter controls (e.g., private APNs) into holistic, real-time monitoring of both network and asset states. Telemetry now feeds directly into AI models, meaning delayed visibility acts as a form of ‘jitter’. Providers must expose programmability via APIs or Model Context Protocol (MCP) servers to enable dynamic policy management, audit trails, and autonomous control loops while maintaining regulatory compliance.
Connectivity is shifting from a volume commodity to an outcome enabler: For MNOs and MVNOs, the commercial conversation must move beyond cost-per-MB towards guaranteed Quality-of-Service, sovereignty-by-design architectures, and operator-led orchestration. Success will be defined by how reliably providers can keep data local, maintain deterministic performance for real-time AI, and offer scalable, compliant global coverage.

Alongside the White Paper, you’ll receive an invitation to our upcoming “Networks for the AI Era: How Connectivity Infrastructure Must Evolve to Meet Enterprise AI Demands” webinar with floLIVE. In this session, we’ll take a deeper look at the challenges of traditional connectivity models and explore how AI can help address them.