AI Answers: How to Earn Citations and Measure Your Visibility

The problem no dashboard solves yet

Measuring AI visibility is now technically possible. Tools like Ahrefs, Semrush and several specialized platforms already track how often a domain is cited in AI-generated answers. However, as highlighted by Search Engine Journal in collaboration with Constance Tan of Ahrefs, most teams can measure AI visibility, but very few manage to move it intentionally.

This is the distinction that matters for an Italian marketing manager or business owner. Having a number on a dashboard isn't enough. You need to understand which variables decide whether a piece of content is cited or ignored by language models. That's why the value of this deep dive lies in turning those variables into concrete actions.

The topic ties directly into the evolution of Google's AI Overviews, which we at SHM Studio have already analyzed in detail in the context of the self-expansion of AI Overviews and its impact on organic CTR. So strategies for earning AI citations aren't separate from traditional SEO: they're its natural evolution.

What AI visibility is, in two sentences

AI visibility measures how often, and in what position, a brand or domain is cited in answers generated by systems like Google AI Overviews, ChatGPT, Perplexity or Copilot. Unlike traditional ranking, it's not about holding a spot in a list: it's about being chosen as a trusted source by a model that synthesizes information for the user.

This distinction has deep operational implications. The criteria an LLM uses to select sources to cite don't exactly match those of Google's ranking algorithm. Likewise, content that performs well in the SERP isn't automatically the content that earns citations in AI Answers.

Three steps to get more citations in AI Answers

Based on Ahrefs' findings and our own operational analyses, we at SHM Studio identify three priority areas for Italian SMEs that want to increase their presence in AI answers.

1. Structure your content as verifiable primary sources

Language models tend to cite content with verifiable claims, original data or authoritative positions on a specific topic. So the first step is to review your existing content through this lens: every key page on your site should answer a specific question directly, with cited sources and up-to-date data.

In particular, the formats that work best are clear definitions, structured lists, FAQs, and paragraphs that start with the answer before developing the reasoning. This approach is consistent with the findings of the Pew study on AI content and its implications for Italian SMEs, which stresses the importance of editorial credibility as a selection factor.

It's also useful to include structured markup (Schema.org) to help crawlers understand the context and type of content. It's not a technical trick: it's a quality signal that AI systems read positively.

2. Build topical authority, not just backlinks

The authority that counts for AI Answers is topical: a domain that covers a specific subject in depth and with consistency is more likely to be cited than a generalist site with lots of backlinks. So your editorial strategy should aim for vertical depth on a few key topics.

This means producing content that links together logically, covers related questions on the same topic, and keeps information up to date. As a result, an editorial plan built around topic clusters, like the one we offer in our SEO copywriting services, becomes the main tool for building this authority.

Topical consistency also helps traditional ranking. So your investment pays off twice: visibility in classic SERPs and citations in AI Answers.

3. Cover the third-party sources the models consult

Language models don't just index websites. They also consult Wikipedia, industry publications, specialized forums, platforms like Reddit and authoritative news sources. So AI visibility also depends on what's written about a brand or domain outside its own site.

In practice, this means taking care of your presence on third-party platforms: updating Wikipedia entries when relevant, contributing to industry publications, taking part in relevant communities. Unlinked mentions, meaning references to a brand without a hyperlink, also carry growing weight in AI systems. As with offline reputation, a consistent message across multiple channels strengthens the authority signal.

This ties directly into the new Google tool for editorial preferences, which lets publishers flag their editorial priorities in response to the drop in traffic caused by AI search.

The metrics that really matter: what to track

Defining the right metrics is the most overlooked step. Many teams just count total citations, but that number alone says nothing about how well your strategy is working. So it helps to structure your monitoring on three distinct levels.

• Citation frequency per target query: how often your domain is cited in AI answers for the company's strategic keywords. This is the main KPI.
• Position in the answer: being cited in the first sentence of an AI Answer is worth more than a mention at the bottom of a list. Position shapes how authoritative the user perceives you to be.
• Referral traffic from AI sources: some platforms, like Perplexity, generate trackable traffic. However, Google AI Overviews doesn't always produce direct clicks, so this data should be combined with brand awareness analysis.

It's also important to track how things evolve over time. AI visibility isn't static: models get updated, sources change, and content that earns citations today may lose relevance tomorrow. So monitoring must be continuous, not occasional.

For the broader context of this shift, read our analysis of how a third of the web written by AI is changing content marketing: a phenomenon that is redrawing the rules of online editorial competition.

The mistakes that wipe out your work

Some common practices in traditional SEO strategies not only fail to help AI visibility, they can hurt it. It's worth knowing them so you can avoid them.

• Generic, undifferentiated content: if an article adds nothing to what's already available online, an AI model has no reason to cite it. Every piece of content needs an original angle, proprietary data or a specific point of view.
• Superficial updates: changing an article's date without updating its content is a practice AI systems can spot. The update has to be substantial and verifiable.
• Overlooking the natural language of questions: AI models are trained on natural-language questions. So content that directly answers "what's the best way to..." performs better than content optimized only for bare keywords.
• Ignoring consistency across channels: if your website says one thing and your social profiles or reviews say another, your authority signal weakens. Just as with personal reputation, consistency is a prerequisite for trust.

Where Italian SMEs should start

For a mid-sized Italian company, tackling AI visibility can feel like a complex project. In reality, the operational priority is simpler: start with an audit of your existing content, identify the pages that cover your business-critical topics, and check whether they answer the questions potential customers ask AI systems in a direct, structured way.

This work fits naturally with an SEO strategy you already have in place. The principles of editorial quality, content structure and topical authority are the same ones that drive traditional organic rankings. So it's not about building a parallel strategy, but about evolving the one you have.

At SHM Studio, we support Italian SMEs on this journey through our AI consulting services and integrated digital marketing activities. In particular, AI visibility work pairs with Google Ads campaigns to ensure an omnichannel presence at the moments when customers make decisions.

For a complete picture of the strategies and tools available, you can explore all our content on the intersection of SEO and AI visibility, where we collect analyses, updates and practical guides on this fast-evolving topic.

If you want to dig into the methodological foundations, the original Search Engine Journal analysis with Constance Tan of Ahrefs is a solid starting point. For anyone managing a company's online presence, ignoring this shift is no longer a viable option.