Agentic AI is moving from research labs into commercial discussions, and the telecom industry is at a critical juncture. At the MWC26 Shanghai AI Core for Agent Communication Network (ACN) Seminar, the message was clear: future mobile networks must become AI-native. But the big question is whether operators will embrace the architectural changes needed to make that leap—or risk falling behind hyperscalers and enterprises that are already moving fast.
What Happened: Agentic AI Takes Center Stage in 6G Planning
The seminar, now in its third year, showcased how intelligent network agents are transitioning from theory to practical implementation. NTT Docomo has prioritized sustainability, efficiency, customer experience, ‘network for AI,’ and ubiquitous connectivity for its 6G core. Orange reported that 150 AI use cases deployed in 2024 generated €200 million in value, and its CogNet project with Nokia Bell Labs and IBM aims to shift network management from reactive to proactive cognitive operations. KPN Fieldlabs is exploring a holistic framework combining service-based architecture (SBA) with AI service management and orchestration (SMO), including an AI core instance with both agent-based and service-based interfaces. These examples show that leading operators are already integrating AI into their core architectures, not just as an overlay.
Why It Matters: The Architecture Choice Determines ROI
The shift from 5G’s data-centric design to 6G’s intent-driven, task-execution model is profound. In a conventional cellular core, NAS (non-access stratum) signaling is rigid and rule-based. In an AI-native 6G core, NAS evolves to support intent-based communication: a device or agent signals its objective, and the network determines how to fulfill it. This creates a direct link between user goals, service logic, and network behavior, enabling proactive coordination of connectivity, compute, security, and latency. Turkcell highlighted its R&D in intent-based communications, studying how dedicated 6G core network functions can handle intent-based requests and how control-plane AI agents affect NAS identifiers and signaling flows. The 3GPP SA2 group is already discussing AI agent roles, resources, and policy access across key 6G architectural issues, including NAS, location services, AI for Network (AI4NET), and data frameworks.
Our Interpretation: A Two-Tier System Looms
XPLAIN AI sees this as a defining moment for the telecom industry. The confirmed fact is that agentic AI is being standardized into 6G core architecture, not as a software overlay. Our interpretation is that operators face a strategic fork: those that redesign their core around AI-native principles will unlock significant ROI, while those that merely use AI to optimize existing domains risk creating a two-tier system where they fall behind. The ROI of agentic AI could be muted if it is constrained to niche applications or deployed as an overlay. True value comes when the core itself is AI-native, allowing agents to interpret goals, find resources, establish trust, coordinate computing, and complete tasks across end users, applications, devices, and networks. This architectural shift is not incremental—it is foundational.
Opportunities and Risks: Winners and Losers in the AI-Native Shift
The move to AI-native 6G will reshape the telecom ecosystem. Potential beneficiaries include:
- Network equipment vendors like Nokia and Ericsson, which are likely to lead in providing AI-based core network functions and intent-based interfaces, creating new revenue streams.
- AI semiconductor and computing companies such as Nvidia, AMD, and Intel, which will see increased demand for high-performance AI chips to handle real-time inference and intent processing. Arm-based server chip developers may also benefit.
- Cloud and edge computing providers like Amazon Web Services, Microsoft Azure, and Google Cloud, along with software firms Red Hat and VMware, as distributed AI agents require robust edge infrastructure and cloud-native orchestration platforms.
On the risk side, traditional telecom equipment makers that fail to adapt could lose market share. Operators that underinvest in AI-native transformation may widen the gap with hyperscalers. Additionally, there is a risk that the transition could create a two-tier system between AI-native leaders and laggards.
Counter-Scenario and Uncertainties
Not all outlooks are bullish. Operators struggled with 5G profitability, and 6G AI-native architecture requires massive network upgrades. If the economic case is not proven, adoption may slow. Standardization delays within 3GPP, security and privacy concerns around autonomous AI agents, and regulatory risks could also hinder progress. Moreover, if AI technology itself develops slower than expected, the promised ROI may remain elusive.
Key Metrics to Watch
Investors should monitor: (1) progress in 3GPP 6G standardization meetings on AI-native architecture key issues; (2) pilot projects and R&D budget changes from major operators; (3) reference architecture announcements and customer wins from equipment vendors supporting AI-native cores; and (4) case studies demonstrating operational efficiency and cost savings from agentic AI. Positive signals in these areas would mark the start of a serious investment cycle in the AI-native 6G ecosystem.
#AgenticAI #6G #Telecom #AINetwork #3GPP #EdgeComputing #AIInfrastructure
Sources
- Network agents are “ready” for commercial use, but are telcos? (Analyst Angle) — RCR Wireless · News coverage · Tue, 28 Jul 2026 10:45:26 +0000
Written by: XPLAIN AI Editorial Team · Reviewed by: XPLAIN AI Editorial Desk
This content was drafted with AI assistance based on publicly available sources and reviewed under XPLAIN AI's editorial standards.