Earlier, SERP’s presence used to be the core aim in digital marketing, but now AI visibility is gradually becoming the new norm.
Although business intelligence has been developing in parallel, the spontaneous takeover of AI is making understanding it more cumbersome.
The major question that digital marketers encounter is how to measure AI visibility and what to focus on.
There is no one-liner answer to this, but a crisp discussion will definitely help in solving this dilemma.
Why Is AI Visibility Accuracy Under Question?
The cause is the algorithm, which varies from platform to platform.
While Google’s AI overview provides source links upfront, ChatGPT and Gemini might provide them infrequently.
Another major point to consider is that search engines work on keywords and the LLMs work on prompts, which are generally lengthy and vary a lot.
Most AI visibility services use the Prompt Tracking Methodology, where a set of possible prompts is executed to find the probability of appearance of your page in citations.
But it can’t be considered a dependable way to provide accurate stats.
Mark Williams-Cook, a highly experienced SEO expert and co-owner of search agency Candour, expressed issues with this methodology in a podcast.
He is of the view that the prompts might vary a lot, and different results will be shown in every attempt. Also, the responses depend on the context and the conversation that the LLM is having with the user.
Another point is that the AI results are non-deterministic, i.e., the response might vary even when the same prompt is executed repeatedly. So a link might not get cited again for the same prompt or query.
Google has also come up with the AI Performance Report in the Search Console, but it provides figures about impressions, not clicks. Also, it only exhibits the data from Google AI features, which limits its scope.
Suggested Reads: Google’s June 2026 Spam Update: Does it Mean AI Manipulation Is Now Officially Spam?
What To Monitor and How?
Changing trends demand new ways to gauge performance over LLMs. Hence, the traditional KPIs or probability-dependent metrics might not work.
Firstly, what needs to be tracked must be ascertained.
- AI Visibility Percentage: Rankings have less relevance in AI visibility, so measuring the percentage appearance in AI responses is desired.
- Multi-platform Analysis: Many LLMs are prevalent in the market, and measuring the performance across all of them can bring a clear image of where the website stands in the competition. Targeting only one platform might not provide accurate figures. Like Google AI reports only provide data about the appearance of Google AI features and not on others.
- Accurate Figures: A good prompt sample needs to be executed to measure the website appearance.
The most widely recommended AI visibility tool here is Semrush, which has an AI visibility toolkit. What makes it special is the multi-engine report that provides visibility into Gemini, ChatGPT, Google AI mode, and Perplexity.
Other suggested noteworthy options are
- SE Visible (by SE Ranking)
- Otterly AI
- Keyword.com AI Visibility
- Scrunch AI
- SE Ranking AI Results Tracker
SEO Community’s Take
Aleyda Solis, a renowned SEO and research consultant, has suggested considering the AI citations (mere appearance in references) and conversions (clicks) through AI platforms as different KPIs. Look at how well she has explained it.
Also, Joshua George, e-com SEO & AI SEO expert, has emphasised brand visibility, traffic, and revenue from LLMs as the key points for measuring success over AI platforms.
Semrush has also supported this wider viewpoint in its post on X, favouring referrals and citations to check a website’s performance.
Bottom Line
AI visibility matters if it remains stable and predictable. If it is not, measuring the performance will be a challenge in itself. So there is a dire need to switch tactics and aim for brand authority and conversions rather than depending solely on getting cited.
The game is changing. The faster you adapt, the better you perform.
