How to think about AEO/GEO in practice
Since the launch of ChatGPT in 2022, consumers have shifted to using LLM platforms like ChatGPT as their preferred information and research tool. As marketers, the shift away from traditional search engines towards AI means one thing: AI systems decide which brands show up, how they are described, and who gets trusted. AEO/GEO (answer engine optimization and generative engine optimization) is how marketers can shape LLM outputs so AI presents your brand accurately and consistently.
What’s Changed
The shift is clear and ongoing.
- AI rewrites the web.
- Brand visibility now depends on:
- Whether content answers questions clearly
- Whether AI understands structure and intent
- Whether the brand is mentioned, trusted, and cited elsewhere
Traditional SEO still matters, but it does not explain how AI systems summarize information or decide which sources to reference. When brands don’t actively participate in shaping LLM outputs, AI fills the gaps using third-party content.
Designing an LLM Program
A durable LLM program focuses on multiple capabilities: owning the questions customers actually ask, making content legible and reusable for machines, earning recognition as a trusted source across the open web, distribution of content, clear semantic links between ideas, and accurate measurement. Together, these form the foundation for reliable visibility in AI-driven answers, recommendations, citations, and business impact.
Content: Own the Questions Your Customers Ask
AI prefers content that is clear, complete, and easy to reuse. That requires covering real questions at every stage of the journey, and not limiting content to awareness topics.
- Focus on full-sentence, intent-driven questions and clear answers
- Source questions from:
- Sales calls and objections
- Support tickets and customer research
- SERP features like People Also Ask
- UGC Forums like reddit, quora, stack overflow
- Keep content fresh, accurate, and updated regularly
- Map content across the full funnel
Start by evaluating whether content reflects how real questions are asked.
Technical: Make Your Site Legible to Machines
AI is capable of evaluating structure before formulating outputs. Inconsistent formatting can introduce ambiguity. Clear and consistent markup allows machines to interpret and reuse content confidently.
Once content exists, structure determines how well machines understands it.
- Apply clear heading hierarchies
- Include metadata that describes content meaning
- Use structured signals like schema to:
- Identify questions and answers
- Separate thought leadership from marketing content
- Clarify entities, topics, and relationships
Keep in mind, structured data is still mostly speculative in terms of LLM citations for GEO and AEO. Regarding semantic web structure and machine readability, the theory that AI will eventually use semantic web elements to associate meaning is sound.
Authority: Be Recognized as a Source
Authority comes from recognition across credible media.
- Encourage positive, plain-text brand mentions
- Gain citations across trusted sources
- Share thought leadership and expert commentary
- Publish podcasts, guest articles, and earned media
- Produce original research and proprietary data
- Maintain presence in forums, Q&A platforms, reviews, and long-form video
Consistent mentions across credible environments establish the brand as a reference source rather than a one-off result. Piggybacking heavily as an extension of SEO, AEO/GEO uses authority as a gauge of confidence when providing answers.
Distribution: Make Answers Portable
AEO does not end on the website. AI systems assemble answers from many surfaces at once.
- Publish answers in formats AI systems frequently reuse:
- Lists
- Comparisons
- Plain-language explanations
- Repurpose core answers into:
- Social posts
- Guest articles
- Community responses
- Maintain consistency across owned and earned channels
AI looks for agreement across sources. Repeated answers across credible environments reinforce which explanations are correct.
Entity Clarity: Be Explicit About What the Brand Is
AI systems reason in entities rather than marketing messages.
- Clearly define:
- The company
- Products and product tiers
- Experts, authors, and spokespeople
- Use consistent naming across content, schema, and external mentions
- Separate factual definitions from positioning language
Clear entity definitions reduce ambiguity and improve attribution inside AI responses.
Measurement: Track What Matters
Measurement must reflect how AI represents the brand.
- Monitor brand mentions inside AI-generated responses
- Track share of voice compared with competitors
- Measure sentiment and factual accuracy of AI mentions
- Evaluate AI-referred traffic quality and conversion behavior
Keyword rankings still provide directional insight, but they no longer tell the full story. Representation and impact matter more than position.
Governance: Maintain Control Over Time
AEO is not a one-time effort. It is an ongoing control system.
- Define which answers the brand must own
- Decide which topics should not be inferred by third parties
- Assign ownership for core definitions and comparisons
- Regularly audit AI outputs for drift or inaccuracies
Without governance, AI narratives slowly diverge from strategy.
Why This Matters
AI search is slowly becoming the default discovery layer. Without active management, brand narratives are shaped by others. Controlling answers leads to clearer explanations, stronger associations, and more predictable demand flow.
The Outcome
A strong AEO program creates clarity and control.
- The brand appears in AI answers
- Representation is accurate and favorable
- Product explanations stay consistent
- Question associations align with strategy
- Demand flows toward the brand in an AI-first world
When AI delivers answers, the brand becomes the reference point. That position builds trust, clarity, and long-term market influence.