It is either too simple or too complex. In both cases, yes.
AI Agents are the new crawlers
If you squint, an AI Agent looks a lot like a traditional crawler. Search engines and analytics tools have always fetched your site from a known set of IPs, on a predictable schedule, for a predictable purpose.
AI Agents do the same thing, but with one important difference. They are driven by user intent.
When someone asks a model a question about your company, your product, or your pricing, that AI Agent may go fetch your site in real time. Not later. Not on a schedule. Right now.
Traditional crawling vs AI Agent behavior
For something like Googlebot, crawl behavior is well understood:
| Site Type | Crawl Frequency |
|---|---|
| High-authority or frequently updated sites | Every few minutes to hours |
| Regular active sites | Daily to every few days |
| Low-traffic or rarely updated sites | Every few weeks or months |
This is predictable and easy to model. AI Agents are different. They are event-driven.
A single prompt like:
Tell me about <your_website>. What does their pricing look like?
Can trigger an immediate request to your infrastructure.
You will see it in your logs:
20.227.140.35 - - [07/Apr/2026:11:15:41 +0000] "GET / HTTP/1.1" 200 6759 "-" "Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko); compatible; ChatGPT-User/1.0; +https://openai.com/bot"
34.34.241.146 - - [07/Apr/2026:11:16:03 +0000] "GET /robots.txt HTTP/1.1" 200 85 "-" "Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; Claude-User/1.0; +Claude-User@anthropic.com)"
This is not fundamentally new traffic. It is just more dynamic, more bursty, and directly tied to user queries.
AI companies self-identify more than you think
A common assumption is that AI traffic is opaque. In reality, many AI companies are quite transparent.
They send clear user agents so you can identify and handle their traffic appropriately. That is important because these companies are not just scrapers. They are also customers.
Here are some examples:
| Company | Bot | Purpose |
|---|---|---|
| OpenAI | GPTBot, ChatGPT-User, OAI-SearchBot | Training, user requests, search |
| Anthropic | ClaudeBot | Training and browsing |
| Google-Extended, Gemini-AI | Generative AI training | |
| Perplexity | PerplexityBot, Perplexity-User | AI search |
| Microsoft | bingbot | Copilot and search |
| Common Crawl | CCBot | Open dataset used across the ecosystem |
Yes, user agents can be spoofed. But reputable AI platforms still self-identify because they want to operate within clear boundaries.
Not all AI traffic is clean
Some AI systems do not make identification easy. You will see generic browser user agents:
Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36
Backed by cloud infrastructure or rotating IP space using residential proxies.
Others distribute requests across a mix of hosting providers and residential proxy networks. This is where things get messy. Attribution becomes difficult, and simple allow or block logic breaks down.
Detection is no longer optional
If you care about how your content is accessed, you need to detect and classify this traffic. At a basic level, you can:
- Inspect user agents
- Monitor request patterns
- Maintain allow and block lists
That works for known actors. It breaks down quickly once traffic becomes distributed or intentionally obscured.
This is where IP intelligence becomes necessary. For example, identifying whether a request comes from a hosting provider, a residential proxy network, or mix of both.
The Max API is designed for exactly this layer of classification.
Attribution is the hard problem
If a request includes a clean user agent, attribution is trivial. If it does not, you are dealing with probabilities.
In real-world datasets, AI workloads often look like a mix of:
- Hosting IPs from cloud providers
- Residential proxy IPs from services like NetNut, OxyLabs or ProxyScrape
- Rapid, asynchronous request patterns
A simple example:
| IP | is_hosting | is_resproxy | resproxy_service_name |
|---|---|---|---|
| 23.26.246.191 | True | False | |
| 69.213.252.246 | False | True | NetNut |
| 73.31.91.242 | False | True | ProxyScrape |
| 142.147.172.32 | True | False |
This is not something you can reliably solve with logs alone.
The takeaway
AI Agents are not fundamentally different from crawlers. They are just faster, more dynamic, and tied directly to user intent. Blocking everything is easy. Understanding what is actually happening is harder. And that distinction matters, especially when the same AI companies crawling your site today may also be your customers tomorrow.