A marketer can do everything right – optimise pages, refine keywords, track rankings – and still miss where discovery is starting to happen. More people are now asking AI tools direct questions instead of browsing search results. They get summaries, comparisons, and brand mentions in a single response, often without clicking through to a website.
That change is forcing marketing teams to look beyond traditional search metrics. Visibility is not only about where a page ranks. It also depends on how AI systems read and present brand information. Tools built around this idea are beginning to appear, reflecting a growing effort to understand how discovery works when answers come from machines not link lists.
AI search doesn’t show pages – it shows answers
In traditional search, appearing on the first page of results could drive visits to a brand’s website. AI search upends that model. When users ask a question like “What’s the best CRM for small business?”, the response they get might include a succinct explanation with or without links. If a brand is named in that response, it has been discovered without a click.
That new mode of discovery has given rise to a concept called Answer Engine Optimisation (AEO). AEO is the practice of organising and presenting information so that AI systems can easily find, understand, and cite it in their responses. Unlike traditional SEO, which focuses on where a page ranks, AEO focuses on how a brand’s content is interpreted and used in the answers these systems generate.
It’s similar to search optimisation, but the goal is visibility inside an answer not below it.
Tools to bridge the gap
Brands that want to show up in AI-generated answers face a new set of challenges. They must make sure their content is easy for machines to parse and that important facts about their products or services are consistent and discoverable. They also need ways to measure how often they are referenced in AI responses.
That’s where tools like EZY.ai come in. EZY.ai is built around the idea that brands need both insight into how they appear in AI search, and practical fixes to improve that visibility. At its core, the platform attempts to connect a website to the world of AI search engines and provide a range of features to help brands be cited more often.
One of the important ideas behind EZY.ai is what it calls an AI Search Visibility Score. The score measures how often a brand’s site or content is referenced by AI systems in response to user questions. That gives marketers a way to track whether their visibility in AI search is growing or slipping.
The platform also helps with structured data, which is a way of adding clear, labelled facts to a site so machines can read them more easily. EZY.ai can generate schema markup and other metadata automatically, which ensures important information – like answers to common questions – is presented in a machine-friendly way.
Beyond that, the tool includes features that generate example prompts and ideal answers tailored to a brand’s site. These are not meant to replace a company’s actual content, but to show how AI systems might interpret questions and how a brand could respond in the way that most accurately reflects its offering.
EZY.ai also tracks AI bot visits – for example, visits from the crawlers used by ChatGPT, Claude, Gemini, and other AI engines. That gives teams data on how often these systems interact with a site, which helps marketers understand where their content is being indexed.
Some versions of the tool even automate parts of the optimisation process. For sites built on platforms like WordPress or Shopify, a plugin can update robots.txt, structured data, and other behind-the-scenes files that influence how easily AI systems can access and use content.
Why this matters now
The reason AEO tools have emerged is not hypothetical. AI search – whether via chat-based interfaces, voice assistants, or integrated “AI Overviews” in traditional search results – is increasingly where users start their discovery. They ask a question and expect a concise, accurate answer. If a brand’s content is missing, unclear, or hard for a machine to parse, that brand may not be cited at all.
For marketers, this presents a new problem. Visibility used to be measured in clicks and rankings. Now, it also includes mentions and citations in AI-generated answers – even if those mentions do not lead immediately to visits. It means understanding not just how users find information, but how machines interpret it.
The change doesn’t mean traditional SEO is dead. Being easy for AI systems to understand still starts with clear, well-crafted content. But brands that ignore how they are represented inside AI answers risk becoming invisible to a growing portion of potential customers.
A wider change in how we think about search
The move toward AI-centric discovery is still young, and marketers are still figuring out the best approaches. Tools like EZY.ai reflect a broader trend: marketers and technologists are trying to bring structure and clarity to a form of search that prioritises answers over links.
Whether AEO becomes a central discipline for every marketing team or stays a niche practice for early adopters, one thing is clear: the way people find information is changing. For brands, adapting to that change means not just ranking higher – but being understood by the software that millions of people use to ask their questions.
(Photo by Aerps.com)
See also: Zeta brings generative AI deeper into marketing operations with OpenAI
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