How to track your visibility in AI engines in 2026

You can only steer what you measure. That is true for SEO, for your campaigns, for your acquisition. It is just as true for your visibility in AI engines, except that for most brands this remains a complete blind spot.

Your customers now ask their questions to ChatGPT, Gemini, Perplexity or Claude, and read a direct answer that cites a few brands. If you do not know whether yours is among them, nor how often, you are ignoring a growing share of your real visibility. Here is what to measure, and how.

What exactly are we measuring

Tracking your AI visibility is not about looking at a ranking. It is about observing, query by query, how the answer engines talk about you. Four indicators really matter.

• The citation rate: across a set of key questions, how often is your brand cited in the answer? It is the equivalent of a presence rate.
• The share of voice: when your brand appears, what place does it hold against the competitors cited in the same answer? Are you the main reference or a mention at the end of the list?
• The wording: how does the model describe you? The context associated with your name (positioning, strengths, caveats) weighs as much as the citation itself.
• The competing sources: which sites and which brands does the model draw on to answer? This is your real competitive landscape on this channel, often different from Google's.

These four angles, tracked over time, paint a faithful picture of your presence in AI answers.

Why it differs from SEO tracking

The natural reflex is to treat AI visibility like position tracking. That is a mistake, for three reasons.

First, there is no position. A search engine returns an ordered list; an answer engine writes a synthesis and slips in a few sources. You are cited or not, but there is no stable "number 3 spot" to monitor.

Then, answers vary. To the same question asked twice, a model may answer differently, cite other sources, rephrase. An isolated measurement means nothing: only repetition over time yields a reliable trend.

Finally, there are several engines, with distinct logics. ChatGPT, Gemini, Perplexity, Claude and Google's AI Overviews do not rely on the same sources or the same criteria. Being cited everywhere by one guarantees nothing with the others. Each engine deserves its own tracking.

The method: key queries, regular tracking, engine by engine

In practice, solid AI visibility tracking rests on three principles.

Start from your key queries. List the questions your customers actually ask around your offer, your category and your competitors. A dozen to twenty well-chosen questions are worth more than a long generic list. These are the ones you will track over time.

Measure regularly, not once. Since answers fluctuate, a single reading is misleading. Periodic tracking, at a constant interval, lets you tell noise from a real trend and see the effect of your content actions.

Separate the engines. Track each question on each engine that matters to you. You will quickly see that your brand can be strong on Perplexity and absent from Gemini, which calls for different priorities.

Done by hand, this exercise quickly becomes unmanageable: re-asking each question, on each engine, at a regular interval, then compiling the results represents considerable and poorly reproducible work. This is exactly the kind of measurement that benefits from being automated. If an engine is missing from your tracking, it can be added on request.

Taking action

AI visibility is not a separate channel to pit against SEO: it is a new angle on the same battle for visibility. Tracking it in the same place as your classic search rankings avoids reasoning in silos and steering blindly.

This is Pulsar's approach: automatic tracking of your citations in the main AI engines, question by question and engine by engine, alongside your SEO tracking and your acquisition. You see, over time, where your brand is cited, where it recedes, and which competitors occupy the ground you are aiming for.

The goal is not to add one more dashboard. It is to turn a blind spot into a tracked indicator, so you can decide which topics to invest in and measure the effect of your efforts.

In summary

AI engines have become a real point of contact between your customers and your brand. Ignoring your presence in their answers means leaving an entire slice of your visibility out of sight. Define your key queries, measure regularly, engine by engine, and connect this tracking to your overall steering. You only steer what you measure: AI visibility is no exception.