Skyword Survey: AI Summaries Blur Brand Distinctiveness

What happened

A new survey from content marketing platform Skyword finds that 45% of US adults could not reliably tell two companies apart when AI-generated summaries described them in strikingly similar language. The research points to a growing risk for brands as AI search tools and chatbots increasingly act as the first — and sometimes only — point of discovery for products and services.

According to CustomerThink's coverage of the findings, the issue is not whether a brand appears in AI-generated answers, but whether what appears is distinctive enough to be remembered. Skyword's research suggests many AI summaries compress brand positioning into generic, interchangeable descriptions, stripping out the tone, detail and differentiation that would normally help a consumer choose one company over another.

Why it matters

As large language models become a default interface for research and purchase decisions, visibility in an AI answer is no longer a sufficient marketing goal on its own. If AI systems summarise competitors in near-identical terms, brands risk losing the one asset that differentiation is meant to protect: a distinct, memorable identity in the customer's mind at the moment of choice.

For experience and marketing leaders, this reframes the task of AI optimisation. It is not enough to be indexed, cited or surfaced by a model — content, messaging and brand voice need to be structured so that AI systems can faithfully carry forward what makes an offer genuinely different, rather than flattening it into commodity language.

By the numbers

• 45% of US adults surveyed by Skyword said they struggled to distinguish between two companies because AI-generated summaries described them in near-identical terms.

The Renascence take

This finding is less about AI accuracy and more about a behavioural risk hiding inside convenience: when a model compresses a brand's story into a tidy summary, it is making a choice architecture decision on the customer's behalf — and most brands have no say in how that compression happens.

The real lesson here isn't "optimise for AI visibility" — it's that distinctiveness has to be engineered into content deliberately enough to survive summarisation. Brands that rely on tone, nuance or implied positioning will get flattened first, because AI systems default to the most generic, most repeated phrasing available. The fix isn't more content; it's sharper, more structurally explicit claims — specific proof points, named differentiators, concrete numbers — that are hard for a model to average away. Any brand treating AI search as just another SEO channel is missing that the stakes are now cognitive, not just technical: lose distinctiveness in the summary, and you lose the decision before the customer even reaches your site.