Is AI Working For Your Organization —
or Feeding Off It?
Score your content architecture against the framework used across 200+ association technology engagements. Receive a personalized vulnerability report.
AI answer engines are consuming organizational content and delivering answers — without attribution, without site visits, and without conversion. Some organizations have built content architectures that make AI work for them. Others are providing free research infrastructure. This assessment tells you which one you are, and what to do about it.
Gap Score
Your Anti-Cannibalization Gap Score (0–100) with a vulnerability rating
Per-Gap Analysis
Ratings across three content architecture dimensions
Layer Distribution
Citation layer vs. conversion layer balance analysis
Prioritized Actions
Top 3 remediation actions personalized to your organization type
No account required. No PII collected for the assessment itself.
Tell Us About Your Organization
These questions personalize your results and recommended actions. They do not affect your Gap Score.
What type of organization are you?
What is your organization's approximate annual budget?
Approximately how many content pages has your organization published?
What is the primary goal of your content program?
How would you describe your organic traffic trend over the past 12 months?
Do you currently monitor what AI answer engines (ChatGPT, Perplexity, Google AI Overviews) say about your organization?
Attribution & Authority Assessment
Evaluating how your content signals credibility to AI answer engines
Attribution & Authority
Content without named, credentialed authors is treated as less authoritative by AI answer engines. Anonymous content gets consumed without attribution — AI cites the content but credits no one, providing no brand or expert recognition for your organization.
Do your highest-traffic content pages have named individual authors?
Do author bylines include verifiable credentials (certifications, years of experience, professional titles)?
Are your content authors' professional profiles (LinkedIn, bio pages) linked from their bylines?
Does your website use structured data (JSON-LD schema) that identifies content authors with their expertise?
When AI engines answer questions about your domain, do the answers attribute your organization or its named experts?
Structure & Extractability Assessment
Evaluating whether your content architecture enables AI citation
Structure & Extractability
AI engines prioritize the first 40–60 words of a page. Content that opens with framing instead of answers gets skipped in favor of competitors who lead with the answer. Structure determines whether your expertise gets cited — or ignored.
Read the first 50 words of your top 3 content pages. Do they directly answer the headline question?
Are your H2 and H3 headings written as questions that match how your audience would search?
How long are your typical content paragraphs?
Can each major section of your content (each H2 block) stand alone as a meaningful, citable answer?
Is your content formatted with structured elements that help AI parse it (clear definitions, short summaries, consistent patterns)?
Decision Layer Presence Assessment
Evaluating whether your content creates a reason to engage — or completes AI's work for it
Decision Layer Presence
If AI can fully summarize your page without the reader needing to visit, the page is too complete. Content without a decision layer functions as free research infrastructure — valuable to AI, invisible to your organization's conversion goals.
Can AI fully summarize your top content pages without the reader needing to visit your site?
How many interactive diagnostic tools does your organization offer (assessments, calculators, scorecards, guided comparisons)?
Do your CTAs promise a specific personalized output, or are they generic?
Does your content explicitly introduce variables that change the answer? ("The right answer depends on YOUR budget, YOUR size, YOUR governance model…")
When a reader finishes your content, is there a clear next step that REQUIRES their organizational context to complete?
Layer Distribution Assessment
Evaluating your citation-to-conversion content balance
Layer 1 vs. Layer 2 Balance
How much of your content is designed to be cited vs. designed to convert? Layer 1 (citation content) feeds AI. Layer 2 (conversion content) creates the engagement AI cannot replicate. The balance determines whether AI is working for you or feeding off you.
What percentage of your published content is purely educational/informational with no conversion layer?
Do your educational (Layer 1) pages explicitly link to or route toward diagnostic tools or interactive assets?
Are your interactive tools and assessments designed so AI cannot complete them on behalf of the user?
Does your content explicitly state what AI can and cannot do regarding your topic?
How would you describe your content's overall architecture?
Analyzing Your Content Architecture
Scoring your responses against the Anti-Cannibalization Content Model™
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Gap Breakdown
Layer Distribution Analysis
Layer 1 (Citation) vs. Layer 2 (Conversion)
Your Biggest Vulnerability
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Top 3 Prioritized Actions
Sector Benchmark
What Comes Next
This assessment identifies your content architecture gaps and highest-priority vulnerabilities. The full remediation roadmap — including competitive benchmarking, content-by-content restructuring priorities, and conversion layer development — requires a SmartThoughts content architecture engagement.
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