I write about trust debt, AI visibility, and why most B2B marketing has been quietly destroying brand equity for twenty years.
WRITER · FOUNDER · SPEAKER
Every thin blog post, oversold campaign, and gated “guide” your marketing team published quietly withdrew from your credibility with the market. For years those withdrawals were invisible — diffuse, forgettable, uncounted.
Then AI consolidated them.
When a buyer types your company name into ChatGPT, the model synthesizes a decade of marketing behavior into a single, on-demand reputation answer. It doesn’t know which posts you meant seriously and which ones you published to hit a keyword. It doesn’t care. It averages everything you’ve ever said and tells the buyer what you are.
I call this Trust Debt. I think it’s the defining unacknowledged liability on the B2B marketing balance sheet, and I think the companies that survive the next five years are the ones who start auditing it now.
In 2019, a buyer asking a peer about your company assembled an impression from three or four touchpoints. Small sample. Forgettable.
In 2026, a buyer opens ChatGPT and gets a reputation built from everything you’ve ever published, every mention on the web, every review that didn’t match your marketing, every LinkedIn post your VP of sales wrote at 11pm. Weighted by what looks authoritative. Delivered in one paragraph.
The signals AI uses to evaluate your brand are almost exactly the same signals that build human trust: authoritativeness, consistency, specificity, third-party validation, demonstrated expertise.
Which means fixing your AI visibility problem and fixing your trust debt problem are the same project. That’s the argument underneath everything I write.
You can’t audit your full trust balance in ten minutes. But you can audit one line item on it — what AI systems actually say about you versus your competitors.
I built the AI Visibility Scorecard to answer three questions:
Across 15 AI-generated prompts a real buyer in your category would type, on the five platforms that matter — ChatGPT, Perplexity, Gemini, Claude, and Google AI Overview.
The Scorecard auto-validates your top competitors and measures your share of AI-generated recommendations against theirs.
Every run ends with a specific outreach and content angle — what kind of authority signal you’re missing, and where to start building it.
Deliverable: A PDF report, generated in ~two minutes, built from 75 live API calls across five AI platforms.
Free. No credit card. Your domain + your top three competitors.
The Scorecard audits one line item. The framework audits the rest.
Most companies have never audited both sides of their trust ledger simultaneously. They know their pipeline metrics. They don’t know their trust balance.
| Trust Assets | Trust Liabilities |
|---|---|
| Original research & proprietary data | Content volume without perspective |
| Citable, publicly documented POV | Inconsistent messaging across surfaces |
| Consistent authorial voice | Claims that outrun actual outcomes |
| Third-party validation | Aggressive lead capture before the buyer’s ready |
| Visible, coherent executive voices | Gated content that didn’t deserve the gate |
| Structured, machine-parseable authority | Cold outreach volume signaling desperation |
| Clear category definition | Org churn visible to the market |
| Reviews that echo the product promise | Reviews that contradict the marketing |
A bad cold email is low-interest — small audience, short memory. A widely-shared LinkedIn post that oversells your product is high-interest — public, citable, and in the training data. A pattern of defensive review responses is compounding-interest — it signals organizational character, not a marketing mistake. A history of rebrands and “new direction” announcements is exponential — it tells AI systems (and buyers) that you don’t know what you are.
Some of your trust debt is cheap to carry. Some of it is quietly destroying your ability to be recommended, referred, or taken seriously.
AI visibility is rented space. You can optimize for it, measure it, get cited by it. I spend a lot of my time helping companies do exactly that — the Scorecard is literally a tool for doing it.
But I think the ultimate goal isn’t to win at GEO. It’s to build brand gravity strong enough that AI recommendations become downstream noise.
When a buyer types your category into ChatGPT, you want to be the answer. But the real victory is when they don’t type the category. They type your name.
Most of my industry is selling a forever-subscription to AI visibility. I’m more interested in the path to not needing one.
Every week I publish one trust asset and one trust liability. Real examples. Mid-market SaaS and B2B services companies, named or anonymized depending on the audit. Over time it becomes a running education in what trust debt looks like in practice.
No pitch, no drip sequence, no gated upsell.
I’m Drew Tracy. I’ve spent the last decade in marketing watching smart teams execute strategies that were quietly destroying the trust balance sheets of the companies they worked for. The frameworks were sound. The playbooks were industry-standard. The execution was sharp. The result was still a slow, invisible erosion of brand equity that nobody could name until AI made it impossible to ignore.
I started writing about trust debt because nobody else was using the right language for what I was seeing. I built the AI Visibility Scorecard because CMOs kept asking me what AI was actually saying about them, and built the Trust Balance Sheet framework because they kept asking for a way to formalize what they already sensed. I keep doing this work because I think the B2B category that figures out how to rebuild brand gravity in the AI era is going to eat the next ten years of the market.
If this argument resonates — or if you disagree with it — I’d like to hear from you: drew@drewtracy.com. For more of my thinking in between, the newsletter is the place.
THE NEWSLETTER IS WHERE THIS CONVERSATION CONTINUES.