Cloudflare提出Agentic Internet:面向AI
The Internet has a second audience
Agent爆发式增长正在重塑Web经济模型,这篇文章清晰阐述了从流量识别到按需付费的商业闭环方案,对关注Agent基础设施和Web变现的从业者极具参考价值。
For most of its history, the Internet had one audience that paid the bills: people. We read the articles, saw the ads, and bought the subscriptions. Bots were always there, but they were mostly large, automated operations that didn't view ads, pay for anything, or read in any meaningful sense.
在其大部分历史中,互联网只有一个为账单买单的受众:人类。我们阅读文章、观看广告并购买订阅。机器人一直存在,但它们主要是大型自动化操作,不查看广告、不为任何东西付费,也不在任何有意义的意义上进行阅读。
That's changing fast. At the end of 2024, Cloudflare handled an average of 63 million HTTP requests a second. Today, it's almost doubled to 115 million, with peaks above 150 million. Over the past year, daily requests from AI agents on our network grew by more than 1,700%. This year, for the first time, more than half of Internet traffic wasn't human.
这种情况正在迅速改变。2024年底,Cloudflare平均每秒处理6300万次HTTP请求。如今,这一数字几乎翻倍至1.15亿次,峰值超过1.5亿次。在过去一年中,我们网络上AI代理发出的每日请求增长了1700%以上。今年,首次有超过一半的互联网流量并非来自人类。
The human web didn't shrink to make room. A second audience arrived alongside it: agents, software acting on behalf of people. They sit somewhere between humans and traditional bots. They don't respond to ads, but there's usually a person behind them with a job to get done. For businesses that learn to serve them and capture value from them, agents are additive. For those that don't, they're extractive.
人类网络并没有缩小以腾出空间。第二个受众随之而来:代理,即代表人类行事的软件。它们处于人类和传统机器人之间的某个位置。它们不对广告做出反应,但通常背后有一个需要完成任务的人。对于学会服务它们并从它们身上获取价值的企业来说,代理是增值的;对于那些没有做到的企业来说,它们是掠夺性的。
What our customers need hasn't changed: to be discovered, to tell great stories, to build great experiences, and to sell. What's changed is that more than half your visitors are now software. Our job is to help you serve both audiences.
我们的客户需求没有改变:被发现、讲述精彩的故事、构建卓越的体验以及销售。发生变化的是,现在你的访客中有一半以上是软件。我们的工作就是帮助你服务这两类受众。
More traffic, less revenue
流量增加,收入减少
For thirty years, the web ran on one arrangement: you let search engines crawl your site, they sent you visitors, and you turned those visitors into a business. Being found and getting paid were the same thing.
三十年来,互联网基于一种安排运行:你允许搜索引擎抓取你的网站,它们将你引荐访客,你将这些访客转化为业务。被发现和获得报酬是一回事。
AI has caused this delicate balance to break down. Now, answer engines read the page and give the reader a summary. This costs websites bandwidth without leading a human to a website where the ads or payments happen. The machines kept coming, and the audience that paid for the web stopped reaching those sites. Some of the most heavily crawled categories, like Retail, Computer Software, IT & Services, and Financial Services, have seen human traffic decline as much as 40% in less than one year.
人工智能导致这种微妙的平衡破裂。现在,答案引擎会读取页面并向读者提供摘要。这消耗了网站的带宽,却没有将人类引导至发生广告或支付行为的网站。机器不断涌入,而为互联网付费的受众群体却不再触及这些网站。一些被爬取最频繁的分类,如零售、计算机软件、IT与服务、金融服务,在不到一年的时间里,人类流量下降了多达40%。
The result is that revenue per request is falling while costs are rising. Every automated request still costs bandwidth, compute, and origin capacity, and a growing share of those requests carry no referral, no ad impression, and no subscription. Our first instinct was to block all automated traffic. Last year we recommended blocking AI training crawlers on new domains so site owners could at least say no to their content being used to build models. In Spring 2025, 22% of the crawler requests we saw were for AI training (according to the crawlers’ stated purpose). By June 2026, it was 52%. The problem is a blanket “no” is not a sufficiently nuanced approach for the Internet economy being built right now.
结果是每次请求的收入在下降,而成本在上升。每个自动化请求仍然消耗带宽、计算能力和源站容量,且越来越多的请求不携带任何引荐来源、广告展示或订阅信息。我们的第一反应是屏蔽所有自动化流量。去年,我们建议在新域名上屏蔽 AI 训练爬虫,以便网站所有者至少可以拒绝其内容被用于构建模型。根据爬虫声明的目的,2025 年春季,我们看到的爬虫请求中有 22% 是为了 AI 训练。到 2026 年 6 月,这一比例已达到 52%。问题在于,对于正在构建的互联网经济而言,一刀切的“拒绝”并非足够细致的策略。
The opportunity is there to cater to agents. Get it right, and you are at the forefront of a new business model. Get it wrong, however, and the results will be the same as they were for generations of websites that were on the wrong side of search engine algorithm changes.
迎合智能体(agents)的机会就在那里。做对了,你将处于一种全新商业模式的前沿;然而做错了,结果将与那些站在搜索引擎算法变更错误一侧的网站几代人一样。
Some of that traffic is a customer
其中一部分流量是客户
An agent booking a table, comparing insurance quotes, or buying a dataset for a researcher is a customer. It just isn't a human one.
预订餐桌、比较保险报价或为研究人员购买数据集的智能体就是客户。它们只是不是人类客户而已。
The fastest-growing part of automated traffic is no longer crawlers. It's agents: software fetching pages on a person's behalf, often because the human asked a chatbot something. That agent traffic follows human routines, with a weekly rhythm and a dip over the summer holidays. Turn an agent away, and you may be turning away the person who sent it.
增长最快的自动化流量部分已不再是爬虫,而是智能体:代表个人获取页面的软件,通常是因为人类向聊天机器人提出了某个问题。这些智能体流量遵循人类的日常习惯,具有每周的节奏和暑期假期的低谷。拒之一个智能体,你可能会同时拒掉发送它的人。
Agents also behave differently from training crawlers. A training crawler collects your pages to build a model. An agent comes back each time someone asks about that content, so this traffic grows with how many questions people ask, not how much you publish.
智能体的行为也与训练爬虫不同。训练爬虫收集你的页面以构建模型。而智能体会在有人询问相关内容时再次访问,因此这种流量的增长取决于人们提问的数量,而非你发布的内容量。
You can't do business with an audience you can't see, can't tell apart, can't set terms for, and can't charge. Until recently, for most of the web's non-human traffic, none of those four things were possible.
如果你无法看见、区分、设定条款并向其收费,你就无法与这样的受众开展业务。直到最近,对于网络中大部分非人类流量来说,这四点都无法实现。
See who’s really visiting
查看真正访问者是谁
"AI bot" no longer means anything useful. What matters is what a bot does. Cloudflare’s AI Crawl Control, Business Insights, and BotBase show site owners who is crawling, what they take, what comes back, and which of your URLs they want most.
"AI 机器人"不再具有任何实际意义。重要的是机器人做了什么。Cloudflare 的 AI Crawl Control、Business Insights 和 BotBase 能够向网站所有者展示谁在爬取、抓取了什么、返回了什么以及他们最想要哪些 URL。
A bot's name is only worth something if you can trust it. With Web Bot Auth, operators, including OpenAI, Google, and AWS, cryptographically sign their agents' requests, so a site can tell a real agent from an impersonator without guessing from IP addresses or user-agent strings. We see more than 500 billion verified bot requests each week.
机器人的名称只有在可信时才具有价值。通过 Web Bot Auth,包括 OpenAI、Google 和 AWS 在内的运营商对其代理的请求进行密码学签名,因此网站无需猜测 IP 地址或用户代理字符串即可区分真实代理与冒充者。我们每周看到超过 5000 亿次经过验证的机器人请求。
Set your terms
设置你的条款
In July, we replaced the single "block AI bots" switch with separate Search, Agent, and Training controls, available on every plan, including Free. The data showed why that distinction was needed. Fewer than 1% of sites on Cloudflare block search crawlers, while 17% block training. Site owners were never trying to hide. But with the rise of agentic traffic and the new ways agents use information, they suddenly had no transparency into, or choice over, how their content was being used. Being found no longer ensures they get paid, and they want to be found without being exploited.
7 月,我们将单一的“阻止 AI 机器人”开关替换为独立的搜索、代理和训练控制选项,这些选项在所有计划中均可用,包括免费版。数据表明了这种区分的必要性。Cloudflare 上不到 1% 的网站会阻止搜索引擎爬虫,而 17% 的网站会阻止训练用途。网站所有者从未试图隐藏其内容。但随着代理流量的兴起以及代理使用信息的新方式,他们突然对内容如何被使用缺乏透明度,也失去了选择权。被发现不再意味着能获得报酬,他们希望在不被剥削的情况下被发现。
That’s particularly difficult in the case of mixed-use crawlers. When one bot does both search and training, refusing one means refusing the other. On September 15, we shipped Disallow AI Training. It keeps you indexed for search while using crawler-specific mechanisms to instruct the operator not to use your data for training. Apple, Google, and Microsoft have committed to honor it. Cloudflare Radar also publicly tracks crawler behavior.
在混合用途爬虫的情况下,这尤其困难。当一个机器人同时执行搜索和训练任务时,拒绝其中一项就意味着拒绝另一项。9 月 15 日,我们推出了禁止 AI 训练(Disallow AI Training)功能。它使你的网站保持索引以用于搜索,同时使用针对特定爬虫的机制指示运营商不要将你的数据用于训练。Apple、Google 和 Microsoft 已承诺遵守该指令。Cloudflare Radar 也会公开追踪爬虫行为。
New domains now see recommended configurations based on how the site makes money rather than what piece of software is visiting. For ad-supported sites, you can easily disallow training and block agents on pages that carry ads, because an ad only pays when a person sees it. You can change any of these settings at any time.
新域名现在会根据网站的盈利模式而非访问的软件类型获得推荐配置。对于依赖广告的网站,你可以轻松禁止训练并阻止携带广告的页面上的代理,因为广告仅在有人查看时才会产生收益。你可以随时更改任何这些设置。
Get paid
获取报酬
In August 2026, we described the Agentic Internet we're building as readable, discoverable, callable, and payable. The last word, payable, is the one that determines whether the open web can fund itself. The web needs a way to say ‘yes, if you pay’ instead of a binary ‘yes’ or ‘no’.
2026 年 8 月,我们将正在构建的代理互联网描述为可读、可发现、可调用的,并且可付费。最后一个词“可付费”决定了开放网络能否实现自我资助。网络需要一种方式来表达“是的,如果你付费”,而不是二元的“是”或“否”。
The licensing market shows both how much demand there is and where the gaps are. More than 50 publisher-AI deals have been signed since 2023. Nearly all of them are bespoke and bilateral, between large publishers and large AI companies. They prove content has value. But they don't reach most of the web, and they don't reach most buyers.
许可市场既展示了需求规模,也揭示了存在的空白。自 2023 年以来,已有超过 50 项出版商与 AI 公司的协议签署。几乎所有协议都是定制化的双边协议,在大出版商与大 AI 公司之间达成。它们证明了内容具有价值。但它们并未覆盖大部分网络,也未触及大多数买家。
Not every asset should be sold the same way. High-value content and datasets need a trusted network, where buyers are identified and report how the work was used. Services like APIs and MCP tools don’t work like that: every request is the use.
并非所有资产都应以相同的方式出售。高价值内容和数据集需要一个可信的网络,在该网络中买家身份可被识别,并报告其如何使用这些内容。API 和 MCP 工具等服务则不同:每一次请求即是一次使用。
So we're building for both.
因此,我们同时为这两种模式构建解决方案。
Pay Per Use reaches the sites that direct licensing can't. Most publishers will never get a bespoke deal with each AI company, and no AI company can negotiate with millions of sites. Pay Per Use is the bridge. It doesn't charge for the crawl. It pays when content is actually used. Every buyer is a verified crawler, which is what makes this a trusted network, and each one defines what counts as use and what it will pay.
按使用量付费(Pay Per Use)触达了直接授权无法覆盖的网站。大多数出版商永远不会与每家 AI 公司达成定制协议,而任何 AI 公司也无法与数百万个网站逐一谈判。按使用量付费正是这座桥梁。它不为爬取行为收费,而是在内容真正被使用时才进行支付。每一位买家都是经过验证的爬虫,这正是其构成可信网络的原因;每位买家自行定义何种行为算作“使用”以及愿意为此支付多少费用。
Publishers see the offer, choose whether to opt in, and are able to opt out whenever it stops working for them. The buyer reports each use, Cloudflare checks those reports, then bills the buyer and pays the publisher. The reporting matters as much as the payment. Publishers see what was used, when and what they earned, and, where the buyer reports it, information about which questions surfaced their work. Licensing deals rarely show any of that. It creates a feedback loop: publishers learn what people are actually asking for, and from that can decide what to cover, what to update, and what to make readily available to agents.
出版商看到报价后,可选择是否加入,并在不再适用时随时退出。买家报告每次使用情况,Cloudflare 核实这些报告,随后向买家计费并向出版商付款。报告环节与支付环节同等重要。出版商可以看到哪些内容被使用、何时被使用、获得了多少收入,以及在买家提供报告的情况下,了解哪些问题展示了他们的作品。授权协议很少提供这些信息。这形成了一个反馈循环:出版商了解到人们实际在询问什么,并据此决定应覆盖哪些领域、更新哪些内容,以及向智能体(agents)开放哪些内容。
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