The Complete
AI Visibility Audit
A comprehensive audit checklist organized across all eight Firefly Framework pillars. Use this to identify exactly where your business is invisible to AI systems, which gaps carry the highest business cost, and where to start the fix.
Work through each pillar section below. For every item, mark it as complete, partial, or missing. Items marked missing are your remediation targets — the gaps that are actively reducing your AI recommendation confidence. Prioritize gaps in earlier pillars (Recognition, Understanding, Discovery) before addressing later pillars (Authority, Citation), because later-pillar improvements deliver less value when earlier-pillar foundations are incomplete.
This audit is designed for self-assessment. For a scored, benchmarked assessment with competitive comparison and prioritized remediation plan, the Firefly site audit applies the same framework with Faeth data and market context.
The Complete Checklist
Count missing items by pillar. The pillar with the most missing items is your highest-priority remediation target — with one exception: if Pillar 1 (Recognition) has any missing items, address those first regardless of counts. Entity ambiguity at the Recognition level suppresses the value of improvements in every other pillar.
AI Visibility Audit — Common Questions
How long does this audit take to complete?
The checklist review itself takes 30–60 minutes for someone familiar with their business's online presence. The AI platform testing component — running the recommended queries across ChatGPT, Gemini, Perplexity, and Claude — adds another 60–90 minutes. Total time investment for a thorough self-audit is 2–3 hours. Businesses with complex multi-location or multi-practitioner situations may require more time to assess NAP consistency and directory presence across all entities.
Should I complete this audit myself or hire someone?
Self-auditing against this checklist is a valuable starting point that gives you a qualitative sense of where your gaps are. The limitation is that self-auditing cannot provide competitive context — you cannot know whether your Citation Share is competitive without testing competitors in the same query set, or whether your pillar scores are above or below market norms without benchmark data. The Firefly site audit provides scored pillar assessments, competitive Citation Share comparison, Faeth-powered analysis, and a prioritized remediation plan — outputs that a self-audit cannot produce.
What score should I aim for?
Completing every item in Pillars 1–5 (Recognition through Discovery) is the minimum foundation for meaningful AI recommendation presence. Pillar 1 and 5 (Recognition and Discovery) items are particularly binary — missing items in these pillars actively suppress AI visibility in ways that partial completion of later pillars cannot compensate for. Treat Pillars 1 and 5 as must-complete before focusing on Pillars 3 and 4 (Trust and Authority), which build on top of a solid foundation.
Related Glossary Terms
The degree to which an AI system can correctly identify, understand, and recommend a business.
The foundational technical and semantic systems that enable AI discovery of a business.
How frequently a business is cited in AI-generated answers relative to competitors in its market.
An AI system's ability to identify a business as a distinct, real-world entity with verifiable attributes.
Schema.org JSON-LD markup that communicates entity identity directly to AI systems.
The primary local entity record AI systems — especially Gemini — use to evaluate and recommend businesses.
Related Framework Resources
Know the Gaps.
Close Them with Firefly.
The self-audit shows you what's missing. The Firefly site audit shows you what it's costing you — with competitive benchmarks, scored pillar assessments, and a prioritized remediation plan.
