Here’s the inconvenient truth: AI search isn’t neutral. It’s already recommending who to buy from, and if you’re not showing up, you’re getting cut out. After watching Marketing Against the Grain, I came away with a simple stance—treat AI search like your new distribution channel or watch revenue drift to your rivals.
This matters because buyers now type real questions into AI tools, not just keywords. They ask for “the best CRM for a 200-person B2B SaaS team,” and the models answer with confidence. If those answers don’t include you—or frame you the wrong way—you lose.
The New Gatekeepers Aren’t Browsers—They’re Models
Kipp Bodnar and Kieran Flanagan make the case plain: AI models set the buying criteria and shape preference before a human ever lands on your site. Their warning hit hard:
“Tools like ChatGPT and Claude are telling your customers to go and buy your competitor’s products or services, and you don’t even know it.”
That’s already happening across ChatGPT, Claude, Perplexity, and Google’s AI mode. Same buyer prompt, different model, different ranking, different reasons. The inputs that drive those answers come from places you can influence: your site, review platforms, Reddit, LinkedIn, YouTube, and earned media.
As Kipp shows, the issue isn’t just visibility—it’s positioning. HubSpot’s service product often gets framed as a CRM add-on, not a true service platform. That’s a story problem, not a feature gap. I’ve seen the same mistake crush good products in crypto, SaaS, and creator tools.
What They Get Right—and Why It’s Urgent
I agree with their core point: brand mentions, category clarity, and review velocity are the new ranking factors for AI answers. Backlinks still matter, but consensus around your brand matters more. And there’s data to back the urgency:
“Over half of buyers are now using these tools to make complex buying decisions.”
If you think your old SEO dashboard covers this, you’re kidding yourself. People now ask long, specific, budget-aware questions. The models try to be helpful, and helpful often means recommending the vendor that the internet already agrees is the safe pick.
My Additions to the Playbook
Their framework is sharp—audits, reviews, PR, research, and fixing broken links. I’d add a few moves I’ve used across marketing and online business:
- Create clean comparison pages: “You vs. Top Rival,” written for humans and AI. Make your edge simple and provable.
- Build proof assets: calculators, ROI worksheets, and pricing clarity. Tools earn links and give models strong anchors.
- Publish customer stories tied to real prompts: “We switched from X to Y because…” Use the buyer’s language in the headline.
- Answer on Reddit, G2, and LinkedIn weekly. Don’t pitch—teach. Mentions compound.
- Add a “Who We’re For” page. Models love crisp fit criteria.
- Use Q&A sections with exact buyer wording. Don’t hide behind jargon.
These steps make your story machine-readable and people-readable at the same time.
How To Start Monday Morning
Don’t boil the ocean. Run a fast, focused sprint that your execs can’t ignore.
- Document 10 buyer prompts that match your best-fit customer. Use your sales calls and support tickets for language.
- Ask the four major AI tools those prompts. Screenshot every answer. Note who ranks, why, and how you’re framed.
- Pick one product line where you’re under-ranked. Identify the root cause: category mismatch, weak reviews, or unclear differentiation.
- Launch a 30-day review drive on 2–3 platforms. Respond to every review. Fix mislabels and categories.
- Ship two high-intent pages: a rival comparison and a “Who We’re For” page. Link them from your nav.
- Publish one proof asset (calculator or data post) and pitch three podcasts or newsletters with that angle.
- Audit and repair 404s and broken internal links. Don’t let models hit dead ends.
This creates a visible shift in how models “learn” your brand without waiting six months for results.
The Line I Won’t Cross
Some will try to game this with fake reviews or AI-spun fluff. Don’t. Models are getting better at sniffing out noise. Real usage, clear value, and steady mentions win. The duo’s example makes that clear: when the story frames a product as an add-on, the rankings follow the story. Fix the story, then the distribution.
The Move Now
AI search has changed the rules. If you’re not training the models on your best story, someone else’s story will train them for you. I’ve built businesses on the back of clear positioning and trusted signals. The same playbook works here—faster.
Run the audit, tighten your category, earn real reviews, publish proof, and speak where your buyers listen. Do it this quarter. Your next customer is already asking an AI for advice. Make sure it says your name—and says it for the right reasons.
