5G networks in the AI era: What you need to know

The increasing deployment of AI applications and new devices is poised to dramatically reshape traffic patterns and capacity demands on 5G networks, creating both challenges and opportunities for mobile operators.

Current state of 5G networks: The widespread deployment of 5G across developed markets has significantly increased network capacity, particularly through Massive MIMO technology which offers up to 10x improvement over 4G capabilities.

• 5G devices typically generate 5-10 times more traffic than 4G devices
• Fixed Wireless Access (FWA) subscribers consume approximately 500GB per month, compared to roughly 50GB for typical smartphone users
• Advanced video codecs have helped some operators see a decline in annual traffic growth

Emerging AI impact patterns: The integration of AI into telecommunications networks is occurring in phases, with early indicators suggesting significant disruption to traditional traffic patterns.

• New AI applications are creating unique traffic profiles, particularly in upload-heavy use cases
• Network automation algorithms require substantial data collection for training purposes
• Third-party AI applications and Large Language Models need to transfer training parameters and collect data from cellular devices

New device challenges: Novel devices entering the market are creating unprecedented traffic patterns that deviate from traditional smartphone usage.

• RayBan smart glasses require 2-15Mbps of uplink capacity for video transmission, with a drastically skewed 1/200 downlink/uplink ratio
• Low-altitude drones for enterprise applications generate heavy uplink traffic through telemetry, images, and video uploads
• These new traffic patterns are pushing operators to reconsider resource allocation, particularly for uplink capacity

Network evolution requirements: The transition to AI-centric networks demands significant infrastructure adaptations.

• 5G-Advanced introduces enhanced bandwidth, capacity, and efficiency improvements
• Edge AI training deployment near data collection points may intensify network demands
• Network operators must invest in upgrades to support new AI applications while maintaining service quality

Strategic imperatives: Mobile operators face crucial decisions in positioning themselves within the evolving AI landscape.

• Operation must proactively manage network upgrades to 5G-Advanced alongside AI adoption
• New business opportunities emerge through specialized service packages for AI-driven devices
• Network customization capabilities open doors for enterprise-specific solutions

Future trajectory and competitive dynamics: The convergence of AI and 5G networks presents a watershed moment for telecommunications providers.

• Failure to adapt network infrastructure could relegate operators to passive infrastructure providers while cloud providers and AI startups capture value
• The shift toward edge computing for AI training could fundamentally alter network traffic patterns
• Proactive infrastructure investment appears crucial for operators to maintain competitive relevance in the AI era

Market implications: The rapid evolution of AI applications and devices signals a fundamental shift in how cellular networks must be designed and operated, with operators needing to balance infrastructure investments against the opportunity to capture value in the emerging AI ecosystem.