Beyond AEO: From Answers to Action
AI visibility uses content to help customers find you. The next opportunity is using business knowledge to help their assistants complete the task.
- Renegade Agency
- Andy Wood
AEO is a useful starting point.
Most conversations about answer engine optimisation (AEO) start with visibility. Does your brand appear when someone asks an AI assistant for a recommendation? Is the description accurate? Does the answer cite your content?
Those questions matter, and the industry is answering them with an SEO 2.0 playbook: publish useful content, structure it clearly, make it crawlable, build credibility.
That helps an organisation enter the conversation. The next opportunity is for businesses to participate in the actions customers want to take next.
Virgin Atlantic’s app in ChatGPT allows customers to explore flights inside the AI assistant conversation.
Imagine three requests made through an AI assistant:
A procurement manager:
“Can you deliver 500 units to our Birmingham plant by Friday, at our contracted price, with the certification this order needs?”
A traveller:
“Move my flight to Friday evening and use my points to cover the difference.”
A parent:
“Am I eligible for help with childcare costs, and can you start my application?”
No web page can answer these. It needs current information, details specific to the person asking, and a way to act.
This depends on two disciplines: data engineering, which makes business knowledge available, and IP management, which sets the terms on which information can be used.
Web page information is limited.
Answer engine optimisation (AEO) helps information appear in direct answers.
It draws on SEO, reflecting the last 30 years of commercial web architecture: organisations publish pages, crawlers discover them, people visit to research, then buy, apply or complete some form of action.
Improving web page sources for AI discovery is a sensible first step.
But the limit is hit when a question needs something more specific than public content can give.
A product page explains what a component does. An airline’s site sets out its change policy. A government page describes who qualifies for social support. But the person asking needs to know what’s available now, what applies to them and whether it can be done by Friday.
Those answers depend on data that changes by the hour, and on details that belong to one customer: a contract, a booking, a household’s circumstances. Even the most frequently updated web page can’t guarantee that an AI assistant has retrieved its latest version.
Public content establishes what an organisation offers.
Connected systems establish what it can do for this person, at this moment.
A web page is only one way to expose information. Inventory systems, product databases, booking platforms, contract records and document repositories all hold knowledge that can determine an AI answer.
Some of that knowledge changes minute by minute. Some is relevant only to a particular customer. Some has commercial value that means it can’t be published on a public web page.
Businesses need AI interfaces that can serve this information selectively, at the moment it’s needed.
From answers to actions.
Today’s customer journey is mostly still organised around people visiting your website.
AI assistants reverse that.
Customers state their goal and it’s the assistant that goes to the organisation on their behalf. It finds options, checks the details and, with access to the right business data and knowledge, can carry out the next action. This might be a purchase, a booking, or an application.
The difference shows in the questions AI assistants are able to answer.
In the table below the left column is AEO/ GEO territory, while the right column is AI-mediated service and commerce:
Left is AEO/ GEO territory. Right is AI-mediated service & commerce.
Answering these next action questions means connecting assistants to the systems where knowledge already lives:
Product and service catalogues
Inventory and booking systems
Customer and case records
Eligibility rules
Document repositories
Websites remain the interface for people. But alongside them, organisations need an interface through which AI systems can request information and perform authorised tasks.
The big opportunity.
Make business knowledge useful to AI assistants at the point of customer decision.
For customers, the payoff is less searching, less repetition and less administration. Their requirements travel with the conversation, from the initial question to an approved next step.
For organisations, it’s an opportunity to respond while someone is ready to act. A supplier can help secure an order, an airline can make a change easier, and a public service can help someone complete an application. Reliable information and easier fulfilment become sources of competitive advantage.
Businesses compete through the quality of their information and the ability to fulfil a request at the moment of customer decision.
The infrastructure is already taking shape.
The infrastructure for assistants to act on someone’s behalf is already taking shape:
OpenAI supports integrations that give assistants access to live business information and controlled actions.
Payment providers are building the transaction layer too:
Stripe has launched a wallet for agents, allowing them to make payments on a user’s behalf without receiving their underlying payment credentials.
Early first example.
Virgin Atlantic’s new app in ChatGPT gives us a glimpse of how these experiences are starting to work. You can ask about flights in ordinary language with ChatGPT, then explore real-time available flight options.
You still jump to the website to complete the booking, but it brings much more of the discovery journey into the AI conversation, and that’s a useful step toward full AI-mediated commerce.
The next step is to make the airline’s knowledge and services available across all AI assistant chats, so customers can complete the booking inside the assistant chat they’re already using.
Virgin Atlantic’s new app in ChatGPT is a useful step toward full AI-mediated commerce.
Start with an AI visibility audit.
AI visibility audit is still a useful starting point. Audits show whether a business appears in answers, how it’s described and where information is missing or inconsistent.
An audit should then lead to questions about the underlying capability:
Where does the correct information live?
Who owns it?
How quickly does it change?
Which parts can be public?
Which require authentication?
What can an assistant do once it receives an answer?
Use the visibility audit to identify priority customer questions,
then build a focused project with the following sequence:
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Choose a use case: identify a decision or action that depends on current, customer-specific or specialist information.
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Map the knowledge: locate the authoritative sources, establish ownership and understand how quickly the data changes.
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Define the sharing rules: decide what’s public, restricted or licensed, who can access it and for which purposes.
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Choose a platform provider: vendors and implementation partners who can connect AI assistants to your existing business systems, and crucially, govern access to proprietary data.
Final thought.
From content presentation to business infrastructure:
The work extends across marketing, technology and operations and moves from content presentation into business infrastructure.
Marketing understands customer questions and brand representation.
Technology teams connect and operate the systems.
Business owners define the meaning of the data.
Governance establishes the boundaries around access and use.
The CMO brings the customer journey, the CTO brings the systems and data, and the CEO connects the capability to growth and service.
It’s a strategic investment that sits in AI transformation, developing foundations for one task that can then support many others.
AEO and GEO help an organisation become part of the answer. The next opportunity is to fulfil the customer intent behind it.
Andy Wood, Strategy Partner
20+ years bringing together business strategy, market insight, and technology to deliver business transformation, customer experience innovation and operational efficiency.
I can help you:
• Deliver next-generation digital experiences for customers
• Align enterprise technologies with operational & strategic goals
• Understand AI across business operations & customer experience
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