AI answers can be manipulated: GEO targets the evidence itself, not the ranking

The real risk of GEO (generative engine optimization) is not gaming search rankings but poisoning the evidence and reasoning behind AI answers. A position paper accepted to ICML 2026 warns that GEO infiltrates the RAG evidence pool and creates three risks — platform concentration, source opacity, and a research gap. As the companion to the previous piece on getting cited, this is the dark side of the same technique. ASAP summarizes the result from the primary source.

What changed — targeting the evidence, not the ranking

The core difference between GEO and SEO is the target. SEO targets the ranking of search results, while GEO targets the evidence pool and reasoning that a generative AI uses to synthesize an answer. Manipulation moves from "which page rises to the top" to "what gets planted in the answer itself."

The three risks

The three risks the paper names are platform concentration, source opacity, and a research gap, all new surfaces absent in the search era. They are summarized as follows.

Risk	Mechanism
Platform concentration	A few generative engines hold most queries, so one platform's manipulation sways public discourse
Source opacity	Data and retrieval processes are undisclosed, so users cannot verify whether the evidence is poisoned
Research gap	Unlike SEO manipulation, academic study is thin, leaving policy and platforms unprepared

The three risks amplify each other. When concentrated platforms hide their sources and research lags, manipulation spreads undetected.

Why it is riskier than the search era

In answer engines, manipulation happens at the answer level, not the page level. In engines that synthesize sources directly, such as ChatGPT Search and Google's grounding search, what the user sees is a single finished answer rather than a list of links. Commercial or malicious information planted in the evidence pool is therefore presented as "the answer" with nothing to compare it against.

How to contain it — three governance levers

The governance the ICML 2026 paper proposes is three levers, each mapped to one of the three risks. The core interventions are as follows.

Promote competition: prevent monopolistic control by a few platforms to reduce the single point of failure.
Mandate disclosure: require platforms to reveal data sources, retrieval processes, and training methods transparently.
Fund research: dedicate academic support to GEO techniques, threats, and defenses.

Each intervention squarely targets concentration, opacity, and the gap in turn.

What it means

The paper is a counterweight for anyone trying to do AEO well. Getting cited (the bright side) and protecting the answer (the dark side) have to advance together. ASAP chasing citations through recency, evidence, and confidence, and keeping that evidence pool from being poisoned through transparent sourcing, are two faces of the same responsibility. Making good content and protecting the answer ecosystem are not separable.

Wrap-up

The risk of GEO lies in the evidence behind the answer, not the ranking. The ICML 2026 position paper names platform concentration, source opacity, and the research gap as the core risks, and proposes competition, disclosure, and research as the three governance levers. In the era of answer engines, "how the evidence is kept clean" matters as much as "how you get cited."

Source: Yizhu Wen et al., "Position: Generative Engine Optimization Creates Underexamined Risks, Governance Must Target Concentration, Disclosure, and Academic Blind Spots" (arXiv 2606.12439, 2026; ICML 2026 Position Track).