The new buyer journey CMOs are missing
Marketing attribution models capture what happens after a buyer identifies themselves. Intent signals, ad clicks, form fills, demo requests. But the decision about which brands to evaluate often happens earlier - in AI - and leaves no trace in your analytics.
A VP of Operations asks ChatGPT for project management software recommendations. ChatGPT returns 4 brands. That buyer visits only those 4 websites and requests demos from 2. Your brand wasn't in the AI response. You never competed. You never knew.
What CMOs need to know about AI search
ChatGPT processes 100M+ queries/day, many of them product research queries
Significant share of your TAM is using AI chatbots for category research
Perplexity is the fastest-growing AI search platform in 2026
Your team needs to track Perplexity separately - it operates differently from ChatGPT
AI recommendations have higher trust than paid ads
Buyers treat AI recommendations as objective third-party guidance - higher conversion than ad-driven traffic
AI consideration sets typically have 3–5 brands
Being #6 in AI recommendations is the same as being invisible - small differences in mention rate produce large differences in pipeline
What CMOs need from AI visibility measurement
Competitive positioning
How does our AI visibility compare to our 3 main competitors? Are we ahead or behind - and is the gap widening or closing?
Category presence
What % of relevant category queries does our brand appear in? For the queries where we're absent, why - and which are highest priority to close?
Framing quality
When we appear in AI responses, are we being recommended or hedged? Is our positioning reflected in how AI describes us?
Trend over time
Is our AI visibility improving quarter-over-quarter? What actions are moving the needle and what is the ROI?
Attribution to pipeline
Can we connect AI visibility to branded search growth, direct traffic, and eventually pipeline? What's the indirect evidence?
Actionable priorities
Which 3–5 changes would most improve our AI visibility? Who owns them and what's the expected impact timeline?
The AI visibility strategy brief for CMOs
AI visibility is not a technical SEO problem. It's a brand authority problem. This distinction matters for resource allocation. The signals that drive AI recommendations are the same signals that build brand authority: being recommended by authoritative third parties, having high review quality and volume, being recognized by analysts and press, and having accurate entity data that reflects your current positioning.
PR and Communications
Editorial placement strategy - which high-authority publications are recommending you, and where are the gaps vs. competitors
Content Marketing
Category authority content and third-party mention strategy - not blog posts, but outreach for editorial inclusion
Customer Success / Product
Review generation - G2, Trustpilot, and category-relevant platforms. Review volume and rating are core AI signals
SEO / Growth
Entity data maintenance (Wikipedia, Wikidata), structured data, and monitoring AI visibility changes with tools like ArtificialPulse
The executive report format
ArtificialPulse's executive-level AI visibility report covers:
AI Visibility Score with competitor comparison (current quarter vs. prior quarter)
Category query landscape - % coverage of relevant queries
Framing quality summary - positive / hedged / negative breakdown
Platform breakdown - ChatGPT vs. Perplexity vs. Google AI Overviews
Top 3 competitive insights (who's gaining, who's losing, why)
Top 3 recommended actions with expected impact and ownership
Get your executive AI visibility brief
Free audit delivers your AI Visibility Score and competitor comparison. Start with data before strategy.