Most B2B buyers have already talked to an LLM before they talk to you. They asked ChatGPT, Claude or Perplexity to explain the category, compare approaches, or name the players worth looking at. By the time they hit your website, the shortlist is half-formed. If you weren’t in the AI’s answer, you weren’t in the conversation.
That’s the AI Demand Channel. Not a tactic. A new commercial layer that sits upstream of search, upstream of your SDRs, upstream of your entire demand gen motion. AI systems — whether a buyer prompting Claude or an autonomous agent doing vendor research — are becoming the first filter in the B2B buying process. Getting found and cited there is the new distribution problem.
This site covers how companies build presence in that channel: through Answer Engine Optimization, content architecture that LLMs can actually cite, and strategies for showing up when AI agents research your category. The frameworks behind this work come from A6 Group. You’ll find links to the relevant methodology throughout.
Start with the fundamentals
What is the AI Demand Channel? — The full commercial journey from AI-powered discovery to purchase decision, and why it changes everything about B2B demand generation.
What is AEO? — Answer Engine Optimization explained: how to structure content so AI systems cite you when buyers research your category.
What is GEO? — Generative Engine Optimization explained: the four-layer framework for building long-term AI authority across content, third-party signals, brand entity recognition, and temporal presence.
The B2B Guide to AEO — A practical how-to guide: which content gets cited by AI, how to structure it for extraction, the gating trade-off, and how to measure your Share of LLM.
The B2B Guide to the AI Demand Channel — End-to-end strategy: baseline audit, AEO foundation, authority signals, Engage layer optimization, measurement framework, and the long game with GEO and Signal-Based Revenue Systems.
Understand the buyer
The AI Buyer Journey — How B2B buyers move from problem recognition to vendor decision entirely inside AI conversations, and when vendors first become visible.
How B2B Buyers Use AI to Build Vendor Shortlists — The shortlist forms before any vendor knows a buyer exists. How it happens and what determines who makes the list.
How B2B Buyers Use LLMs to Find Vendors — The specific queries, behaviors, and patterns buyers use when researching vendors through AI Search tools. Most of it is zero-click research that leaves no trace in your analytics.
How AI Agents Research Vendors — What autonomous AI agents actually do when evaluating vendors on a buyer’s behalf, and what they can and cannot access.
How to Engage with AI Agents as a B2B Vendor — The vendor-side response: what agents prioritize, how to structure your digital presence for autonomous evaluation, and how to prepare for agent-to-agent interaction.
Measure and act
How to Build a Query Library for AEO — The five query categories every B2B company needs to track, how to size and run your library, and how to turn monthly results into content decisions.
How to Measure Share of LLM — A practical guide to building a query library, running tests across LLMs, and interpreting results against competitive benchmarks.
Share of Voice vs Share of LLM — Why your traditional brand metrics have zero visibility into the channel where buyers form vendor preferences. Includes LLM Position and AI Brand Presence as the qualitative dimensions traditional metrics miss entirely.
The 5 AEO Metrics Every B2B Marketing Team Should Track — Share of LLM, LLM Position, citation accuracy, query coverage, and citation source mix — and how to use them together.
AEO vs SEO — What changes and what stays the same when you optimize for AI citation rather than search rankings.
AEO vs the AI Demand Channel — Citation does not equal customer. Why AEO is the on-ramp and the AI Demand Channel is the highway — and what it costs to stop at AEO.
Optimize and improve
How to Structure Content for AEO Citation — The six structural principles that make B2B content citable by AI: question-first headings, front-loaded answers, self-contained statements, specific claims, terminology consistency, and clean HTML.
The AEO Trifecta: Relevant, Authoritative, Extractable — A three-part diagnostic framework for identifying exactly where your AEO strategy is failing and what to fix first.
How to Audit Your AI Brand Presence — A five-step audit using free AI platforms and a spreadsheet to reveal how AI systems currently describe and position your company.
Why Your Best Content Is Invisible to AI — The three structural barriers that prevent good content from getting cited: gating, JavaScript rendering issues, and terminology inconsistency — and how to fix each.
Which Sources Should You Focus On for AEO? — The five-tier source hierarchy for building third-party authority: from analyst reports and review platforms to industry publications and community presence.
AEO for B2B SaaS — How software companies get cited by AI: the query types SaaS buyers run, the content types that get cited most, and why technical documentation is your biggest untapped AEO asset.
AEO for B2B Cybersecurity — How security vendors get cited by AI: the compliance-first query pattern, why certification pages are gating criteria, and the content types that drive citations in security categories.
How to Build an AI-Friendly Content Architecture — The three content tiers that drive citation coverage, integration page strategy, hub-and-spoke internal linking, and how to identify and fill content gaps using buyer query mapping.
AEO vs GEO in Practice — What you actually do differently: which activities are AEO, which are GEO, which serve both, and how to prioritize based on your resources and current performance gaps.
Glossary
AI Demand Channel · AEO · AI Brand Presence · AI Buyer Persona · AI Discovery · AI Search · AI Visibility · Agentic Buyer Research · Buyer Intent Signal · Citation Accuracy · Citation Source Mix · Dark Funnel · GEO · LLM Citation · LLM Position · Prompt Engineering for AEO · Query Coverage · Share of LLM · Signal-Based Revenue System · Zero-Click Research