How to Audit Your Competitors' AI Visibility
Before you can improve your own AEO, you need to know what's working for the brands already appearing in AI answers. This is how to run a structured competitor AI audit.
Most AEO work starts in the wrong place. Teams focus on their own content and visibility before understanding what's actually driving their competitors' AI presence. The result is effort spent in the wrong direction.
A competitor AI audit changes that. It tells you which brands own which queries, what sources AI engines draw from when citing those brands, and where the gaps in their coverage are. That's the foundation for a strategy that competes on facts rather than guesses.
What a competitor AI audit tells you
Running queries manually through ChatGPT, Perplexity, and Gemini reveals several things at once.
Who appears for each query tells you which brands AI engines treat as authoritative in your category. Which sources get cited tells you what type of content those engines trust. How a competitor is described tells you what attributes AI engines have associated with their brand from reading third-party sources.
Together, those three observations let you reverse-engineer why a competitor shows up and what you would need to build to compete. Understanding the mechanics behind their presence is covered in why your competitors show up in AI answers and you don't, but the audit is how you discover whether those mechanics are actually at work for a specific brand.
Which queries to run
Start with the queries your potential customers are most likely to ask before they know your brand exists.
Category queries follow the form "best [product type] for [use case]" or "top [category] tools." These show which brands are positioned as category leaders. Comparison queries like "[Competitor A] vs [Competitor B]" or "alternatives to [Competitor A]" reveal how AI engines frame your competitors' positioning and weaknesses. Problem queries like "how do I [solve specific problem]" show which brands AI engines recommend as solutions.
Run at least ten queries, spread across all three types. Use different phrasing for the same intent. AI engines do not return identical answers to synonymous queries, and a brand may appear for one phrasing but not another.
What to record for each query
Create a simple log. For each query, record which brands appear, what the engine says about each brand, and which sources it cites (look for footnotes, links, or attribution text).
The sources section is the most valuable part of the log. If a competitor consistently gets cited through G2 reviews, that tells you something about what the engine treats as authoritative for that category. If citations come from a specific trade publication or roundup page, that tells you where to focus your own distribution effort.
Note the exact language AI engines use to describe competitors. That language comes from specific sources, and understanding which attributes get attached to which brands reveals what each brand has done to shape its AI presence. A competitor consistently described as "the easiest tool to set up" has built that association somewhere, and your log will help you trace it.
How to identify source gaps
Once you've run your queries and noted the cited sources, look for two things: sources your competitors own that you don't, and sources nobody in your category has yet.
Sources competitors own that you don't are your most direct improvement targets. If a specific review platform, roundup, or publication consistently appears in their AI citations and not yours, that's a gap you can close. Getting on the same platform, or into the same type of publication, directly addresses the asymmetry.
Sources nobody has yet are opportunities. If AI engines consistently cite the same two or three sources for your entire category, and those sources don't cover the specific use case where your product wins, that's a gap you can fill with content no competitor has produced. AI engines fill citation gaps with the best available source. If you write it, you own it.
How to map a competitor's AEO position
After collecting data across multiple queries, patterns emerge. A competitor may dominate category queries but appear rarely for specific use-case queries. Another may appear in comparison queries but never in problem-solution queries.
Map each competitor against the query types you ran. Mark the queries where they appear consistently, occasionally, or not at all. That map tells you the shape of their AI visibility: where they're strong, where they're exposed, and where you have an opening.
Consistent appearance across many query types signals broad authority. That takes time to build against. Spotty appearance concentrated in one query type signals narrow positioning, which means you can compete effectively by covering the query types they've left open.
Turning the audit into action
An audit without follow-through is just data collection. The output should be a short list of specific actions, ordered by impact.
If a competitor appears in a roundup that you're not in, that's an outreach task. If they get cited through review content on a platform where your profile is thin, that's a review acquisition task. If their citations come from a type of content you haven't produced, a case study or original research piece, that's a content creation task.
Prioritize the actions where the gap is small and the potential impact is direct. Getting into one source that's already being cited is faster than building a new type of source from scratch.
How to track AEO performance over time explains how to set up a tracking system so you can measure whether closing these gaps is actually moving your AI visibility. Run the same queries after each major change and compare against your baseline.
How often to run a competitor audit
The first audit is the most valuable because it establishes the baseline. After that, a light version every quarter is usually enough.
A full re-audit makes sense when you launch a new product, when a new competitor enters your category, or when your own AI visibility changes significantly. AI engines update their knowledge continuously, and a competitor who wasn't appearing six months ago may have built enough signal to show up consistently now.
The audit is also the fastest way to detect when a competitor makes a significant AEO move. A new publication featuring them, a spike in review volume, or a new roundup placement will show up in query results before it shows up anywhere else.
QuickAEO lets you run structured audits across ChatGPT, Perplexity, and Gemini without manually querying each engine, so you can see competitor visibility and source patterns across all three in a single view.