Microsoft outlines the key factors for AEO and GEO and provides three practical strategies for being recommended by AI assistants.
Microsoft has released a sixteen-page guide that explains how to optimize for AI search and chat. While many of the recommendations can be categorized as SEO, some tips are specifically related to AI search interfaces. Below are the most valuable insights.
Understanding AEO and GEO and Their Importance
Microsoft clarifies that AI search interfaces have led to a shift from 'ranking for clicks' to 'being understood and recommended by AI.' Traditional SEO still serves as a basis for being referenced in AI, but AEO and GEO are crucial in determining whether content is featured in AI-driven environments.
Microsoft differentiates between AEO and GEO. Notably, they define AEO as Agentic Engine Optimization, which differs from the more commonly understood term Answer Engine Optimization.
AEO (Answer/Agentic Engine Optimization) emphasizes the optimization of content and product information to facilitate easy retrieval, interpretation, and presentation by AI assistants and agents as direct responses. GEO (Generative Engine Optimization) aims to enhance the discoverability and persuasiveness of your content within generative AI systems by improving clarity, trustworthiness, and authority.
Microsoft perceives AEO and GEO as relevant not only to marketing but also to various teams across an organization.
The guide states:
"This transition affects every aspect of the organization. Marketing teams need to reconsider brand differentiation, growth teams must adjust to AI-driven pathways, ecommerce teams are required to evaluate success in new ways, data teams should highlight richer signals, and engineering teams must ensure that systems are both AI-readable and dependable."
AI shopping is not merely a single channel; it represents a collection of interconnected systems.
Microsoft characterizes AI shopping as comprising three interconnected consumer touchpoints:
AI browsers that interpret the content of a page and provide context as users navigate.
AI assistants that respond to inquiries and facilitate decision-making during conversations.
AI agents capable of performing actions such as navigating, selecting options, and completing transactions.
The significance of the AI touchpoint is secondary to the system's ability to access accurate, structured, and reliable product information.
SEO Still Plays A Role
According to Microsoft’s guide, the competition between AEO and GEO transitions from discovery to influence. While SEO remains relevant, it is no longer the sole focus.
The emerging competition centers on influencing the AI recommendation layer, rather than merely achieving high rankings.
Microsoft articulates this as follows:
SEO aids in product visibility.
AEO enables the AI to articulate it effectively.
GEO ensures the AI trusts and endorses it.
Microsoft further clarifies:
"The competition is evolving from discovery to influence (SEO to AEO/GEO).
Whereas SEO aimed at generating clicks, AEO is concentrated on enhancing clarity through enriched, real-time data, and GEO is dedicated to establishing credibility and trust so that AI systems can confidently recommend your products.
SEO continues to be fundamental, but succeeding in AI-driven shopping experiences necessitates assisting AI systems in comprehending not only what your product is but also why it should be selected."
How AI Systems Decide What To Recommend
Microsoft elaborates on how an AI assistant, specifically Copilot, processes a user's request. When a user seeks a recommendation, the AI assistant enters a reasoning phase, breaking down the query by utilizing a blend of web and product feed data.
The web data supplies:
"General knowledge
Category comprehension
Your brand positioning"
The feed data includes:
"Current prices
Availability
Key specs"
Based on this feed data, the AI assistant may opt to highlight the product with the lowest price that is also available in stock. When the user navigates to the website, the AI Assistant examines the page for contextual information.
Microsoft provides the following examples of context:
Detailed reviews
Videos that explain the product
Current promotions
Delivery estimates
The agent compiles this information and offers insights regarding what it has found concerning the product's context (such as delivery times, etc.).
Microsoft summarizes it as follows:
Initially, there is crawled data:
The information that AI systems acquire during training and retrieve from indexed web pages, which influences your brand’s foundational perception and serves as a basis for AI responses, including your product categories, reputation, and market position.
Next, there are product feeds and APIs:
The structured data that you actively submit to AI platforms, allowing you to control how your products are depicted in comparisons and recommendations. Feeds ensure accuracy, detail, and consistency.
Finally, there is live website data:
The real-time information that AI agents observe when they access your actual site, encompassing rich media, user reviews, dynamic pricing, and transaction capabilities. Each data source has a specific function in the shopping journey — traditional SEO remains crucial because AI systems conduct real-time web searches frequently throughout the shopping process, not solely at the time of purchase, and your site must achieve a high ranking to be found, assessed, and recommended.
Microsoft advises a Three-Part Action Plan
Strategy 1: Technical Foundations
The fundamental concept of this strategy is that your product catalog should be machine-readable, consistently presented across all platforms, and regularly updated.
Key actions:
Utilize structured data (schema) for products, offers, reviews, lists, FAQs, and brand information.
Incorporate dynamic fields such as pricing and availability.
Ensure that feed data and on-page structured data are in sync with what users actually observe.
Prevent discrepancies between visible content and what is delivered to crawlers.
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Strategy 2: Optimize Content For Intent And Clarity
This strategy focuses on refining product content to effectively address common user inquiries and facilitate ease of reuse by AI.
Key actions:
Craft product descriptions that begin with benefits and real-world use-case value.
Employ headings and language that align with how individuals pose questions.
Incorporate modular content blocks:
FAQs
specifications
key features
comparisons
Add Contextual Information
Facilitate multi-modal interpretation (effective alt text, transcripts for video content, structured image metadata).
Provide complementary product context (pairings, bundles, “goes well with”).
Strategy 3: Trust Signals (Authority And Credibility)
The essential takeaway from this strategy is that AI assistants and agents favor content that appears verified and credible.
Key actions:
Enhance review credibility (verified reviews, substantial volumes, clear sentiment).
Bolster brand authority through real-world indicators (press coverage, certifications, partnerships).
Maintain claims that are grounded and consistent to prevent trust erosion.
Utilize structured data to clarify legitimacy and identity.
Microsoft articulates it as follows:
“AI assistants prioritize content from sources they can trust. Signals such as verified reviews, review volume, and clear sentiment help establish credibility and influence recommendations.
Brand authority is strengthened through a consistent identity, validation in the real world such as media coverage, certifications, and partnerships, as well as the implementation of structured data to distinctly define brand entities.
Claims must be factual, consistent, and verifiable, since exaggerated or misleading information can undermine trust and restrict visibility in AI-driven experiences.
Takeaways
The objective of AI search shifts from achieving rankings to obtaining recommendations. While SEO remains important, AEO and GEO play a crucial role in how effectively content is interpreted, articulated, and selected by AI assistants and agents.
AI shopping is not merely a single channel; it constitutes an ecosystem of assistants, browsers, and agents that depend on authoritative signals derived from crawled content, structured feeds, and live site interactions. The brands that succeed are those that maintain consistent, machine-readable data and provide clear content that includes valuable contextual information that can be easily summarized.
Microsoft has published a blog post that includes a link to a downloadable explainer guide titled: From Discovery to Influence: A Guide to AEO and GEO.
