3 New GEO Frameworks for AI Marketing
Between September 16 and 22, 2026, Search Engine Land published three separate frameworks for generative engine optimization (GEO) in the space of a single week — a sign of how fast the category is still forming. None of them has settled into an industry standard yet, but each is worth knowing by name, because these are the terms likely to show up in vendor pitches and agency decks soon.
Three Pillars: LLM Readability, Brand Context, Agentic Commerce
The first framework groups GEO work into three pillars. LLM readability covers the technical and structural side — writing and formatting content so language models can parse and extract it cleanly, similar in spirit to how you'd optimize for a featured snippet, but broader. Brand context refers to keeping consistent, accurate information about your company across the web so AI systems build a correct picture of who you are and what you offer. Agentic commerce is the newest and least defined of the three: as AI agents start completing purchases and bookings on a user's behalf, it points to optimizing not just for being mentioned, but for being the option an agent actually selects and transacts with.
That third pillar is worth watching closely even though it's early — it's a meaningfully different problem from getting cited in a written answer.
The "ASC Framework" for Becoming the Cited Answer
A second piece introduced what Search Engine Land is calling the ASC framework, aimed at helping brands become the answer AI systems surface rather than just one of several sources they draw from. The publication hasn't yet established this as a widely adopted methodology, and the specifics are still shaking out — treat it as an emerging approach to track rather than a settled playbook to implement wholesale.
A Three-Layer Approach to AEO Attribution
The third framework tackles a problem every team doing AEO work runs into eventually: proving it worked. It proposes measuring AI-era search visibility across three layers rather than a single metric, aiming to connect citation events back to actual traffic and conversion outcomes. Attribution has been the weak point of AEO reporting so far — this is one of the first attempts to formalize it into something repeatable rather than one-off analysis.
Why This Is Happening Now
The backdrop explains the urgency. Google AI Overviews appeared in 39.4% of U.S. desktop searches in June 2026, up from 25.8% a year earlier — and being used as a source doesn't guarantee getting credit for it. TripAdvisor, for instance, was used as a source in 61% of lodging-related AI answers but only received a visible citation in 21% of them. With the stakes that high and rising, it makes sense that multiple frameworks are racing to define best practice at once.
The Takeaway: Track, Don't Commit — Yet
Three competing frameworks emerging in one week is a sign of a category still finding its footing, not a sign that any one of them is right. The practical move is to watch which of these gets picked up by other publications and practitioners over the next month or two, rather than rebuilding your GEO strategy around whichever one you read first. If you want a lower-risk starting point in the meantime, the fundamentals covered elsewhere in this series — clean content structure, credible sourcing, and consistent brand information — hold up regardless of which framework eventually wins out.