Academician Forecasts Sharp Decline in Conversational AI Traffic by 2030, with Agent Services Dominating

Deep News
昨天

At the opening of the 2026 China Internet Conference, a keynote address was delivered on the topic of AI-native reconstruction of the internet.

The speaker noted that while large language models have initiated a new AI era, they excel at general understanding but lack precision for specific, niche tasks. Intelligent agents have emerged to fill this gap, though a single agent can only handle simple tasks, with complex operations requiring multi-agent collaboration. The formal arrival of the intelligent internet will occur with the mass connection of agents, creating a new system of multi-agent cooperation in an open environment.

A forecast was presented indicating global IP traffic is expected to reach between 5.5 and 7 zettabytes per month by 2030, growing at an annual rate of 60% to 90%, with AI agent traffic accounting for 60% of the total. The structure of traffic is also set to shift significantly. Traditional consumer application traffic, which comprised 47% to 58% in 2025, is projected to fall below 30% by 2030. Intelligent computing traffic, at 30% to 35% in 2025, is predicted to rise to between 45% and 55%. The remaining traffic will flow to data circulation infrastructure. Within computing traffic, the proportion from model inference is forecast to exceed 60% by 2030, surpassing that of model training.

Regarding the domestic trend for token-based traffic, conversational token traffic, which made up about half of the total in 2025, is predicted to constitute only 12% by 2030. In contrast, the share of traffic from intelligent agents and their services is expected to surge to 75%.

The address highlighted that the immense demands for bandwidth, low latency, and computing power are compelling a comprehensive transformation of internet architecture. The traditional internet connected hosts and information, whereas an AI-native internet extends to connecting agents and capabilities. The concept of AI-native involves embedding intelligent computing power inherently within the network system, rather than adding it as an external layer afterwards.

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