An AI authority score is a single number — typically on a scale of 0 to 100 — that quantifies how prominently and consistently a business appears across AI-generated answers. It provides a benchmark for tracking progress over time and identifying where to focus content strategy for maximum impact.
Why a single score is useful
AI visibility is complex. A business might be strongly cited by Perplexity but invisible to Claude. It might own brand queries but be absent from competitive queries. It might be well-represented in its core service category but missing from adjacent market queries.
A single authority score distils all of that signal into one number that answers the most important question: overall, how well is this brand represented when AI engines answer questions in this space?
That single number also enables the most valuable measurement activity: trend tracking. A brand that goes from 41 to 67 over three months has measurably improved its AI visibility. That's a metric you can report to a client, a board, or a marketing team.
How an AI authority score is calculated
Different tools calculate AI authority scores differently. The AiVIS methodology is based on three layers:
Layer 1: Narrative scoring per query
For each query run through the AI engines, the brand's presence in the response is classified into one of five narrative states: Owned, Weak, Contested, Lost, or White Space. Each state carries a different numerical weight:
Owned — full credit. Your brand is the clear answer.
Weak — partial credit. Mentioned but not prominently.
White Space — zero credit for now, but flagged as opportunity.
Layer 2: Confidence weighting
Not every query produces a consistent answer. When AI engines give contradictory responses across multiple runs — one engine says Owned, another says Lost — the score is weighted by the confidence of the consensus. High-agreement results carry more weight than ambiguous ones. This prevents outliers from distorting the overall score.
Layer 3: Pillar weighting and commercial relevance
Not all queries matter equally to a business's bottom line. A query about brand history carries less commercial value than a query about pricing, capabilities, or "best [service] for [use case]". AiVIS assigns a revenue weight to each query (1–5 scale, where 5 is highest commercial intent) and incorporates pillar weights to produce a revenue-weighted authority score alongside the base score. This ensures the metric reflects business impact, not just presence.
The result is a score from 0–100 where each point represents real, weighted AI visibility — not a vanity metric. A score of 70 means the brand is prominently cited across the majority of commercially relevant queries in its space.
The five visibility pillars
Authority scores are also broken down by pillar, so you can see exactly which areas are strong and which need work. The five pillars are:
Brand
Queries directly about your company — name recognition, reputation, founding story, leadership. This pillar measures entity clarity.
Expertise
Queries about thought leadership and specialisation — "who are the experts in X?" or "who should I follow for advice on Y?"
Service
Queries about your category of product or service — "best [service type] for [customer type]". Highest commercial intent pillar.
Market Position
Queries about your industry and where your brand fits — "leading companies in [market]", "who dominates [segment]?"
Competitive
Head-to-head queries — "[your brand] vs [competitor]" and "alternatives to [competitor]". Shows how AI frames you relative to rivals.
What does a good AI authority score look like?
Benchmarks vary significantly by industry, brand age, and market size. As a general guide:
0–25
Critical
Largely absent from AI answers. Competitors are capturing this space. Immediate content and citation-building work required.
26–50
Developing
Present in AI answers but inconsistently. Brand queries may be owned but service and competitive queries are being lost.
51–70
Established
Solid AI presence. Most brand and expertise queries owned. Competitive pillar likely still contested — the main growth area.
71–100
Dominant
Category-leading AI visibility. Named across most query types including competitive. Brand is the default AI answer in its space.
Most businesses starting their AEO journey score in the 20–45 range. A score above 65 typically requires deliberate, sustained content and citation work over several months.
Which levers move the score most
Not all actions move the authority score equally. Based on what consistently drives score improvements across AiVIS users, the highest-leverage activities are:
HIGH
Publishing content that directly answers LOST and White Space queries
The fastest way to move from Lost to Owned on a specific query is to publish a piece of content that directly, authoritatively answers that question and associate it with your brand. This is why source intelligence — knowing exactly which queries you're losing — is so valuable.
HIGH
Building review platform presence
For web-grounded engines (Perplexity, Copilot), third-party reviews are the most trusted source. 20 detailed reviews on G2 or Capterra can move multiple service pillar queries from Lost to Contested or Owned within one scan cycle.
HIGH
Earning coverage in "best of" lists and comparison articles
When AI engines answer "what's the best X?", they frequently synthesise from top-ranking comparison articles. Outreach to secure placement in these articles — or publication of your own well-optimised comparison content — directly feeds citation behaviour.
MEDIUM
Structured data implementation
Adding Organization, FAQ, and Product JSON-LD schemas helps AI engines understand your entity and content. Typically a one-time technical improvement that has a durable, compounding effect — particularly for Gemini.
MEDIUM
Community engagement (Reddit, forums)
Authentic mentions of your brand in community discussions feed both training data and real-time retrieval. Slower to build but high-quality — community endorsement is one of the most trusted signals for AI engines.
How often should you measure your AI authority score?
The right cadence depends on how actively you're executing an AEO strategy. For most businesses:
Monthly — the minimum useful cadence. AI engine behaviour shifts with model updates; monthly scans catch significant changes.
Fortnightly — appropriate when actively publishing content targeting specific gap queries. Fast enough to see the impact of individual pieces.
Weekly — suited to agencies tracking multiple clients or businesses in fast-moving competitive markets where competitor activity shifts frequently.
The most important thing is consistency — comparing scores from the same query set, same engines, same methodology. Ad hoc measurements with different parameters aren't comparable and don't produce the trend data that makes the score actionable.
Get your AI authority score in minutes
AiVIS runs 50 queries across up to 5 AI engines, scores every result, and produces your authority score, pillar breakdown, and a content plan to improve it. Free to start.