Does GEO work? The evidence is weaker than the pitch

A 45-study review challenges many of the claims surrounding generative engine optimisation (GEO). So, does GEO work? The evidence supports some practices, questions others, and rejects several promises commonly used to sell GEO services.

Generative engine optimisation has become one of the fastest-growing services in AI search. We sell it ourselves, which gives us a commercial reason to repeat the category's favourite claims and a stronger reason to correct them before a client does.

Generative engine optimisation (GEO) refers to improving how content is retrieved, cited, and presented by AI-powered search and answer engines.

A critical survey of 45 GEO studies reached an uncomfortable conclusion: current evidence on generative engine optimisation does not show that any evaluated technique consistently improves discoverability, traffic, or business outcomes across AI platforms.

The distinction changes the answer to the central question: does GEO work? Some interventions can improve how retrieved content is used. The research does not yet support a dependable formula for getting retrieved in the first place, remaining visible across platforms, or turning citations into revenue.

The GEO 40% visibility claim needs its footnote

The original GEO paper reported visibility gains of up to 40%. The figure is valid within that experiment. It has since travelled much further than the methodology allows.

The experiment supplied a fixed set of sources to the model before measuring citation prominence. It did not test whether an unseen webpage could be discovered, retrieved, or clicked in a live commercial AI search engine.

The 2026 survey therefore treats the GEO 40% visibility claim as post-retrieval evidence rather than proof of improved discoverability.

Citation counts also deserve caution. A Nature Communications study evaluating medical questions found that 50% to 90% of LLM responses were not fully supported by the sources they cited. That benchmark should not be generalised to every market, though it shows why “we gained more citations” cannot stand alone as a business result.

For organizations asking, "does GEO work?", the evidence points to an important distinction. Current research is stronger at showing how content performs after it has been retrieved than how reliably it gets retrieved in the first place.

Is generative engine optimisation worth it?

Questions about whether generative engine optimisation delivers measurable results are no longer confined to academic research.

In July 2026, one r/SEO discussion described AEO and GEO as buzzwords designed to trick clients. Another called GEO techniques and visibility monitoring “pretty much all snake oil”. The language was harsh, but the underlying complaint was fair: agencies often sell certainty where the measurement remains noisy.

Generative engine optimisation is worth funding when the expected outcomes are clearly defined. It can improve content quality, reduce factual inconsistency and create cleaner answer units for systems that have already found the page. It can also reveal how a brand is described across AI platforms.

Investment becomes harder to justify when vendors promise stable citation gains from generic formatting changes or present a single visibility score as though every AI platform behaves the same way. The value lies in improving content quality and measurement, not in promising predictable visibility gains.

This leads naturally into the next section, "What actually holds up in GEO," because the reader is now asking, if those promises don't hold up, what does?

What actually holds up in GEO

Across multiple client engagements in LexiConn, three practices have consistently delivered value despite the limitations in today's generative engine optimisation evidence.

1	Answer genuine buyer questions Across multiple client engagements, three practices have consistently delivered value despite the limitations in today's generative engine optimisation evidence.

2	Create self-contained answer blocks Self-contained answer blocks also improve readability for human visitors, making the investment valuable even as AI platforms evolve.

3	Measure platforms separately Use the same prompt set across multiple testing rounds, then compare trends by platform instead of relying on a blended visibility score.

Several common GEO promises are not supported by current evidence. We will not sell guaranteed GEO uplift, promises that FAQs or comparison tables trigger retrieval, blended visibility scores that hide platform differences, or forecasts that citations automatically become traffic and revenue.

So, does GEO work? Yes, but only within specific stages of the discovery pipeline. The generative engine optimisation evidence supports careful testing, stronger information architecture and better measurement. It does not support a universal playbook.

Taking this position may cost an easy sales pitch, but it builds long-term credibility with clients who eventually review the same research.