AI agents will be your next customers – is your website ready?

A quiet revolution is underway

Imagine you run a shop on a busy high street. You've designed an elaborate window display, hung beautiful signs, and every day customers walk in, browse, compare and buy. So far, the world we know.

Now imagine that, starting tomorrow, a large part of your potential customers no longer walk through the door themselves. Instead they send a delegate: an AI agent that visits dozens of shops at once in a fraction of a second, compares prices and terms, evaluates documents – and then makes a buying decision. Without looking at your window. Without reading your signs. Without being impressed by your beautiful website.

That's exactly what is beginning to happen online. And most companies, websites and online shops have no idea yet.

Sources: Imperva/Thales Bad Bot Report 2025 (51% automated traffic in 2024, mostly scraper bots) · Stripe Agentic Commerce Suite. Autonomous shopping agents are a small but the fastest-growing share of non-human traffic today.

Who are these AI agents anyway?

AI agents are no longer science fiction. You meet them daily: ChatGPT searching for information on its own. Claude writing code and calling APIs. Codex or Hermes working through tasks autonomously. These are the visible heralds of a bigger wave.

Soon every person will have several personal agents – for shopping, travel booking, research, financial decisions. Every company will run business agents: a procurement agent that compares suppliers and negotiates contracts. A support agent that handles tickets and processes refunds. A CFO agent that evaluates twelve software vendors at once and recommends the one that fits internal policies.

These agents don't behave like humans. They have no patience for beautiful design. They aren't convinced by testimonials. They don't scroll through your product video. They want one thing: structured, machine-readable information – instantly.

How an AI agent buys – the Agent Buying Journey

To understand what changes, we need to grasp how an AI agent actually "buys". On the surface the process resembles human buying – but the decisive differences are in the detail:

• 1
  Find: agents don't read websites, they parse structures

  An AI agent doesn't search with Google. It asks other AI systems (Perplexity, ChatGPT with web access) or reads machine-readable files directly. It wants to know: what can you do? At what price? Which interfaces do you offer? A website without structured metadata simply doesn't exist for it.

• 2
  Evaluate: no gut feeling, only criteria

  The agent reads API docs, machine-readable price lists, technical specs. It doesn't compare intuitively – it compares algorithmically. Which offer best meets the given criteria? Beautiful design is irrelevant. A clear, structured capability description is everything.

• 3
  Trust: policies and identity, not testimonials

  Before an agent acts, it checks: am I allowed to? Is this service trustworthy? What are the usage limits? It looks for explicit policies, identity protocols (OAuth), sandboxes to test in. A "500+ happy customers" banner won't convince it.

• 4
  Buy: with its own wallet, spending limit and audit trail

  With Stripe's Agentic Commerce Suite, agents get access to stored wallets – with spending limits, approval rules and a full audit trail. A purchasing agent only buys if the price is within budget and the billing is auditable. Your checkout has to be technically accessible for that.

• 5
  Use: tool calls instead of UI clicks

  A human clicks through your interface. An agent calls an API. It doesn't want a pretty UI – it wants MCP tools, SDKs and endpoints. A SaaS service without machine-readable access simply won't be used by an agent.

• 6
  Recommend: agents tell other agents what works

  Perhaps the most alien aspect. Agents share "experiences". An agent that successfully used a service recommends it onward – or warns against it. This is the basis for an entirely new kind of word-of-mouth in the machine-to-machine economy.

What agents need – and what your website lacks today

The question is simple: what do agents need that humans don't? The answer defines the infrastructure gaps emerging right now:

The new currency: machine readability

In the old web, attention was the scarce resource. You fought for it with good design, persuasive copy, testimonials, SEO rankings. The human who landed on your page had to be convinced.

In the Agent Web, machine readability is the scarce resource. An agent can't be convinced – it decides based on structured data. If it can't evaluate your offer in a fraction of a second, it moves on.

From SEO through GEO to AEO

For a generation of online entrepreneurs, SEO was everything: rank well on Google, win organic traffic, optimize conversions. That discipline isn't dying – but it's being complemented. The first step was GEO (Generative Engine Optimization): making sure AI assistants like ChatGPT and Claude cite and recommend you.

AEO – Agent Engine Optimization – goes a step further: shaping your content, structures and interfaces so AI agents can not only find and understand you, but also use you and execute transactions.

You don't need to rebuild your website today. But you should start building an agent layer now – in parallel to your existing human-facing surface.

Five things to do differently right now

1. Replace forms with tool calls

Every form is a dead end for an agent. Consider which actions (contact, booking, support) you can offer as an API endpoint or MCP tool an agent can call directly.

2. Build a capability manifest, not just a landing page

A landing page convinces humans. A capability manifest informs agents: what can you do? With which inputs and outputs? What costs and limits apply? Structured and machine-readable – not in marketing language.

3. Create an llms.txt for your domain

The llms.txt standard (analogous to robots.txt) is a machine-readable file that tells AI systems what your service does, what documentation is available and how it can be used. The simplest, most effective step you can take today. Whether your robots.txt even lets AI crawlers in takes 20 seconds to check with the robots.txt AI check.

4. Provide executable support – not just docs

An agent can't "read" a FAQ page and act on it. It needs endpoints that perform actions: start a return, create a ticket, query status, reschedule. Invest here and you also save staffing costs – agents then handle support workflows end to end.

5. Think about agent analytics

The next generation of analytics captures agent behavior: which agents called my API? What did they ask? Where did they fail on missing information or inaccessible endpoints? This data is gold.

What's at stake – and who wins

The machine-to-machine economy isn't a niche topic for tech startups. It affects everyone selling products or services online: e-commerce shops, SaaS providers, agencies, freelancers, local businesses.

Think of a travel agent that books a hotel room on behalf of a customer, changes the reservation, arranges the transfer and adds everything to a calendar – autonomously, in seconds. Which hotel does it book? The one with the prettiest website? Or the one whose booking system is directly accessible to agents?

The urgency: why now?

First: the infrastructure is forming now. Stripe launched its Agentic Commerce Suite with agent wallets in December 2025. Anthropic, OpenAI and Google are building agentic systems already in use today. The infrastructure for the agent economy is emerging right now – not in five years.

Second: early adopters define the standards. Whoever builds their llms.txt now, structures their API documentation and creates a capability manifest will show up in the data of the next agent generations. That's the new first-mover advantage.

Third: the effort is still manageable today. Agent optimization currently takes a fraction of the effort of classic SEO work. The more companies start, the more competitive it gets. The best time was yesterday – the second best is today.

Your first step: the llms.txt

You don't need to rebuild your entire infrastructure today. But you can take one step that works immediately. The llms.txt lives at yourdomain.com/llms.txt and tells every AI system in machine-readable form:

• ✓What your service or company does
• ✓What documentation is available and where it lives
• ✓Which interfaces and tools you offer
• ✓Which terms of use and limits apply
• ✓Which languages, markets and capabilities are supported

Here's what a lean llms.txt looks like in practice:

Think of the llms.txt as your business card for AI agents. Just as robots.txt tells crawlers what they may do, llms.txt tells agents what they can do with you. Check yours with the llms.txt validator.

Sources & evidence: Imperva/Thales Bad Bot Report 2025 · Stripe Agentic Commerce Suite (Dec 2025). Forecasts are labeled as such.