What Is Agent Traffic? How AI Agents Generate Internet Traffic
Agent traffic is created when AI software acts on a user’s behalf, calling models, websites, APIs and other tools while it works through a task.
Agent traffic is network activity generated when an AI agent takes actions for a user or application rather than simply returning one model response. The agent may call an AI model, visit websites, query APIs, search databases, retrieve documents and then make more model calls before the task is finished.
That means one visible user instruction can create many separate machine-to-machine requests behind the scenes. This “fan-out” is what makes agent traffic different from a simple chatbot request.
How an AI agent creates traffic
A normal AI chat request can be relatively linear: send input to a model and receive a response. An agent adds a control loop. It can decide what to do next based on the result of the previous step.
The agent sends the original request to a model and receives a plan or next action.
It calls a tool, website, API, database, browser or another service. This creates additional network traffic outside the original model connection.
The result comes back. That response may contain text, structured data, files, status information or an error that the agent must interpret.
The agent sends new context back to a model to decide whether the task is complete or another action is needed.
The cycle can continue several times. More complex tasks generally create more model calls and more network interactions.
Inference traffic is inside agent traffic, but it is not the whole thing. Each time the agent asks a model what to do next, that is an inference request. The website visits, API calls and tool traffic around those model calls are additional agent-generated traffic.
Why agent traffic can multiply quickly
The important network effect is that users no longer have to make every request themselves. The agent can keep working at software speed after the human has stopped clicking.
Cisco reported in September 2026 that tasks performed by AI agents generated up to 450% more total network traffic than traditional user-driven workflows in its testing. Cisco also said about 70% of that tested agentic traffic was attributable to AI inference.
This is not a claim that every agent always uses 450% more bandwidth. It shows how quickly traffic can expand when a task becomes a chain of model calls and automated actions rather than a single human-driven request.
Cisco’s figure comes from testing cited in its 2026 network research and September 2026 reporting. Results depend on the task, tools used and number of agent steps.
Cisco’s broader WAN research describes agents as network “power users” because they operate at software speed. Its modeling says enterprise traffic could grow much faster as agentic workflows become more common, although those long-range projections should be read as scenarios rather than measured current traffic.
Agent traffic vs. inference traffic vs. crawler traffic
These terms are often grouped together as “AI traffic,” but they describe different network behavior.
| Traffic type | What triggers it | What it does | Typical pattern |
|---|---|---|---|
| Inference traffic | A model receives an input. | Processes the request and returns a generated result or prediction. | Input travels to the model; output tokens or media return. |
| Agent traffic | A user or application delegates a task to an agent. | Uses models and tools to complete multiple steps. | Model calls, web/API requests and repeated loops until completion. |
| Search crawler traffic | A crawler indexes content for discovery. | Scans pages so search or AI search systems can find them later. | Background crawling across many pages. |
| Training crawler traffic | A crawler collects content for model development. | Fetches material that may be used to train or fine-tune models. | Broad collection rather than immediate user-directed action. |
Akamai formalized a similar distinction in September 2026 when it split its AI Bot category into training crawlers, AI search crawlers, and AI fetchers and agents. Akamai says fetchers and agents access websites on an ad hoc basis to fulfill immediate user requests or complete tasks on their behalf.
Our separate guide to inference traffic explains the model-request part in more detail, while AI traffic covers the wider mix of inference, agents, crawlers and data movement.
Agent traffic can start as human traffic
Another reason agent traffic is harder to classify is that a session can switch between human and machine activity. Cloudflare calls this a form of hybrid traffic.
A shopper might browse a site manually, hand a checkout or comparison task to an AI assistant, then return to review the result. From the website’s perspective, one customer journey can contain both human requests and agent-generated requests.
That matters for websites because blocking every bot can also block useful user-directed agents. Cloudflare and Akamai are both adding more detailed classifications so site owners can distinguish a real-time agent working for a user from a training crawler collecting content in the background.
Why agent traffic matters to networks and websites
Agent traffic changes the relationship between a user action and the network work that follows. A person may send one instruction, but the infrastructure can see many requests from that one task.
More requests per task
Agents can create multiple inference sessions, website fetches and API calls from one user instruction, increasing traffic without an equivalent increase in human clicks.
Demand becomes less predictable
The number of steps depends on the task. Some jobs finish in one or two calls; others loop across many services before returning a result.
Sites need better bot classification
A user-directed shopping or research agent has a different purpose from a training crawler, making blanket bot rules less useful.
Machine-speed actions need limits
Agents can interact with services faster than people, so authentication, authorization, rate controls and clear tool permissions become more important.
Cloudflare says billions of well-behaved bot requests are already spent re-fetching pages that have not changed, which is one reason it is promoting more agent-friendly ways to make content readable and callable. The long-term goal is to reduce wasteful browsing behavior and let authorized agents interact with sites more directly.
Agent traffic is not automatically malicious traffic. Some agents are directly acting for a user. The challenge for sites and networks is telling useful, authorized agent activity apart from abusive automation, scraping and attack traffic.
The bottom line
Agent traffic is the network activity created when AI software takes a multi-step task and starts making requests on a user’s behalf. That can include inference calls, web page fetches, APIs, database queries and repeated model interactions.
The important difference is fan-out. One human instruction can create many machine-generated requests, which is why agentic AI can increase network demand faster than the number of people using the service. It is also why websites increasingly distinguish user-directed agents from ordinary crawlers and other bots.
Agent traffic FAQs
What is agent traffic?
Agent traffic is network activity generated when an AI agent acts on behalf of a user or application. It can include model inference requests, website fetches, API calls, database lookups and repeated machine-to-machine requests while the agent completes a task.
Is agent traffic the same as crawler traffic?
No. Crawlers usually scan or index content in the background. AI agents and fetchers can access websites and services in real time to fulfill an immediate user request or carry out an autonomous task.
Sources
- Akamai: AI training crawlers, AI search crawlers, fetchers and agents, September 3, 2026
- Cloudflare: Building an open Agentic Internet, August 6, 2026
- Cloudflare: Good and bad behaviors on the Agentic Internet, August 7, 2026
- Cisco: The Impact of AI on Wide Area Network Traffic, 2026
- Cisco: Agent tasks and network traffic growth, September 21, 2026