Domain Authority is dead. Not because Moz said so, but because the metric was built for a world where humans clicked through ten blue links. That world is gone. In its place, a new measurement has emerged: Share of Model, the probability that an AI recommends your brand when a user asks a relevant question.
What Is Share of Model?
Share of Model (SoM) is the percentage of times your brand appears in AI-generated responses across a set of representative queries for your category. Unlike Domain Authority, which estimates your likelihood of ranking on Google, Share of Model directly measures whether AI systems like ChatGPT, Perplexity, Gemini, and Claude mention you when potential customers ask questions you should be answering.
Think of it this way: Domain Authority was a proxy. It predicted visibility. Share of Model IS visibility. There is no prediction involved. You either appear in the AI’s answer or you do not.
The metric works by running a statistically significant number of queries across multiple AI models and measuring how often each brand gets cited or recommended. The result is expressed as a percentage. If your brand appears in 34 out of 100 relevant AI responses, your Share of Model is 34%.
Why Domain Authority Stopped Matter
Domain Authority was introduced in the late 2000s as a way to estimate how well a page would rank on Google. It worked because Google’s algorithm relied heavily on link equity, and DA was a reasonable proxy for link strength. For over a decade, it was the north star metric for SEO teams worldwide.
Three things broke that model:
AI search overtook traditional search behavior. ChatGPT alone processes roughly 64.5% of all AI search sessions as of March 2026, according to Stackmatix market share data. Combined with Gemini at 21.5%, AI search now handles 45 billion sessions monthly. None of those sessions use link equity to determine what to show.
Zero-click became the default. Bain research found that 80% of consumers rely on zero-click AI results at least 40% of the time. Seer Interactive analyzed 25.1 million Google AI Mode impressions and found 93% of queries end without a click. If nobody clicks, your DA score does not matter.
AI citation logic is fundamentally different from ranking logic. Google ranks pages based on backlinks, relevance signals, and user behavior. AI models generate recommendations based on entity recognition, structured data availability, content extraction quality, and training data exposure. A site with DA 85 can be invisible to ChatGPT if its content is not structured for AI extraction.
The 2026 AI Search Visibility Report from Omniscient Digital, which analyzed over 23,000 LLM citations, found that 92% of brands are completely invisible in AI search. Many of those brands have strong Domain Authority scores. They rank well on Google. They just do not exist in AI recommendations.
How Share of Model Is Calculated
The calculation is straightforward, but the methodology matters.
Step 1: Define your query set. Select 50 to 200 queries that represent how real users search for your category. These should be natural language questions, not keyword-stuffed phrases. “What is the best project management tool for small teams” not “project management software best.”
Step 2: Run queries across models. Submit each query to ChatGPT, Perplexity, Gemini, and Claude. Record every brand mentioned in the response, including the position (first mention, second, etc.) and context (recommended, mentioned, compared).
Step 3: Calculate per-model share. For each model, divide the number of queries where your brand appears by the total queries. If ChatGPT mentions you in 40 out of 100 queries, your ChatGPT Share of Model is 40%.
Step 4: Weight by market share. Multiply each model’s SoM by that model’s market share to get a weighted overall score. ChatGPT carries more weight than Claude because more people use it.
Step 5: Track changes over time. Run this weekly or monthly. Track directional movement. A 5-point swing in Share of Model over 30 days is significant.
Share of Model vs. Domain Authority: A Side-by-Side Comparison
| Dimension | Domain Authority | Share of Model |
|---|---|---|
| What it measures | Link-based ranking potential | Actual AI recommendation frequency |
| Data source | Backlink index | AI model outputs |
| Granularity | Per-domain or per-page | Per-brand, per-category, per-model |
| Speed of change | Slow (weeks to months) | Can shift within days |
| Predictive? | Indirect proxy | Direct measurement |
| Covers AI search? | No | Yes, exclusively |
The key difference is that DA is an indirect proxy built on third-party link data, while SoM is a direct measurement of what AI systems actually output to users. One guesses. The other observes.
Why Share of Model Matters for Every Business
If your customer asks ChatGPT “what is the best [your category] tool” and your brand does not appear, you have already lost that customer. No amount of Google ranking will fix it because the customer never goes to Google. The AI was the entire journey.
This is not a future scenario. It is happening right now. The 2026 AI Search Visibility Report evaluated 14 GEO services and found that the vast majority of brands have zero AI presence. They invested heavily in SEO, built backlink profiles, and optimized for Google. And it worked, for Google. But AI models use different signals entirely.
Share of Model gives you a metric that aligns with how discovery actually works in 2026:
- Board-level reporting. “Our Share of Model increased from 12% to 31% this quarter” is more meaningful than “our DA went from 45 to 52.”
- Competitive benchmarking. You can see exactly how often competitors appear in AI recommendations versus your brand.
- Channel attribution. If AI referrals are growing (and they are, up 520% year-over-year per multiple industry reports), SoM tells you how much of that growth you are capturing.
- GEO optimization feedback. Change your content structure, deploy llms.txt, add FAQ schema, then measure if your SoM moved. This is the closed loop that SEO always wanted but never fully had.
The Signals That Drive Share of Model
Based on the data from the Omniscient Digital study and searchless.ai’s own analysis of AI citation patterns, three signals dominate:
1. Entity Authority (Mentions Across 6+ Domains)
AI models learn about your brand from the broader web. If your brand is mentioned on multiple independent domains in contexts relevant to your category, AI models associate your brand with that category. This is not the same as backlinks. A nofollow mention on a high-traffic publication does more for your Share of Model than a dofollow link on a random blog.
The threshold appears to be around 6 to 8 independent domains mentioning your brand in relevant contexts. Below that, AI models have weak entity associations. Above it, citation probability increases significantly.
2. Answer-First Content Structure
AI models extract the first one to two sentences of a response 73% of the time, according to multiple extraction studies. If your content buries the answer three paragraphs deep, the AI will find a source that leads with it.
Answer-first means: the very first sentence of your article, section, or paragraph directly answers the question. Context, nuance, and supporting arguments come after.
3. Structured Data and llms.txt
ChatGPT reads JSON-LD schema. Perplexity parses FAQ structured data. llms.txt provides a machine-readable map of your content. Brands with all three of these in place have measurably higher Share of Model scores than brands that rely on traditional HTML content alone.
llms.txt adoption is still below 5% of websites. That means implementing it today is a fast, low-effort way to differentiate your AI visibility from competitors who have not bothered.
How to Measure Your Share of Model Today
You do not need expensive tools to get started. Here is a practical approach:
Quick manual audit (30 minutes):
- Write down 20 questions your customers would ask an AI about your category.
- Type each one into ChatGPT, Perplexity, Gemini, and Claude.
- Record whether your brand appears and in what position.
- Divide mentions by total queries across all models.
This gives you a rough baseline. It is not statistically rigorous, but it will tell you whether you are at 0%, 5%, or 40%. For most brands, the answer is closer to 0% than they expect.
Automated tracking: Tools like searchless.ai’s AI Visibility Score automate this process across hundreds of queries and multiple models. The advantage is consistency, statistical significance, and longitudinal tracking. You get a number you can compare week over week.
For a free starting point, you can run an AI Visibility Score at audit.searchless.ai in about 60 seconds.
The Competitive Landscape: Who Is Winning Share of Model
The Omniscient Digital report reveals an interesting pattern. The brands winning Share of Model are not always the brands winning Google rankings. They tend to share these characteristics:
- High content velocity. Publishing daily or near-daily keeps brands in training data refreshes and citation pools.
- Multi-format presence. Brands that appear in articles, podcasts, YouTube transcripts, and social media have richer entity profiles for AI models to draw from.
- Structured and extractable content. Sites with clean HTML, proper heading hierarchy, FAQ sections, and schema markup get cited more often because AI models can extract answers with confidence.
- Cross-domain mentions. Being talked about on other websites, even without links, builds the entity associations that drive AI recommendations.
Notably absent from the winning formula: backlink quantity, exact-match anchor text, and page authority scores. The signals that built the SEO industry are not the signals that build Share of Model.
From SEO KPIs to GEO KPIs
If your marketing dashboard still tracks Domain Authority, keyword rankings, and organic click-through rate as primary KPIs, you are measuring the past. Here is what a modern GEO dashboard looks like:
| Old SEO KPI | New GEO KPI |
|---|---|
| Domain Authority | Share of Model |
| Keyword ranking position | AI citation frequency |
| Organic sessions | AI referral sessions |
| Backlinks acquired | Entity mentions gained |
| Click-through rate | AI recommendation position |
| Pages indexed | llms.txt coverage |
This is not about abandoning SEO. Google still drives significant traffic, and will for years. But if your measurement framework only accounts for Google, you are blind to the fastest-growing discovery channel in history.
What to Do This Week
Three actions that will move your Share of Model within 30 days:
Run a baseline measurement. Use the manual method or a free tool to find out where you stand. You cannot improve what you do not measure.
Implement llms.txt. It takes less than 30 minutes. Less than 5% of websites have one. This is the lowest-effort, highest-impact GEO action available today.
Restructure your top 10 pages for answer-first content. Rewrite the opening sentence of each page to directly answer the primary question. Move supporting context below.
These three steps alone can shift your Share of Model by 10 to 20 points within a month, based on patterns we have observed across searchless.ai users.
FAQ
What is Share of Model?
Share of Model (SoM) is the percentage of AI-generated responses that mention or recommend your brand across a representative set of category queries. It measures your actual AI visibility, not an estimate.
How is Share of Model different from Domain Authority?
Domain Authority estimates your Google ranking potential based on backlink data. Share of Model directly measures whether AI models like ChatGPT, Perplexity, and Gemini recommend your brand. DA is a proxy. SoM is a direct measurement.
Why should I care about Share of Model?
Because 900 million people use AI search weekly, and 92% of brands are invisible in AI recommendations according to the 2026 AI Search Visibility Report. If AI does not mention you, those users never find you. Share of Model tells you whether you exist in the AI discovery channel.
How do I measure my Share of Model?
Run 20 to 50 relevant queries across ChatGPT, Perplexity, Gemini, and Claude. Count how many times your brand appears. Divide by total queries. For automated tracking, use a tool like searchless.ai’s AI Visibility Score.
What drives a higher Share of Model?
Three primary signals: entity authority (mentions across 6+ independent domains), answer-first content structure, and technical readiness (llms.txt, FAQ schema, clean HTML). Brands with all three have significantly higher SoM than those relying on traditional SEO signals alone.
Is Share of Model replacing SEO metrics entirely?
Not yet. Google still drives traffic, and traditional SEO metrics still matter for that channel. But Share of Model is the primary metric for AI visibility, and AI visibility is the fastest-growing discovery channel. Smart teams track both.
The brands that measure Share of Model today will be the brands that dominate AI recommendations tomorrow. Domain Authority served the industry well for over a decade. But the search landscape has fundamentally changed, and the metrics need to change with it.
Find out where you stand. Get your free AI Visibility Score in 60 seconds at audit.searchless.ai.