Content Strategy for AI
Writing for AI Extraction
Problem-first language
The most citable content starts with the buyer's problem, not your solution. "We built the most powerful CRM for modern sales teams" tells AI models very little about when to recommend you. "If you're a 10-person startup trying to close deals without enterprise complexity" tells the model exactly which buyers to surface you for.
Rewrite your homepage headline. Your product description. Your G2 profile summary. Lead with the problem. The AI will match you to the buyers who have it.
Direct recommendation copy
AI models learn from patterns in text. If content around your brand consistently uses recommendation language — "teams like X use [Brand] because...", "the best option for early-stage startups is..." — the model learns to associate you with that recommendation context.
This is why getting recommended by others (in reviews, in newsletters, in community posts) is more powerful than saying it yourself. But saying it yourself, consistently and specifically, still matters.
Structured clarity
For AI engines that crawl the web, content structure matters. Use clear headings. Write concise paragraphs. Put the key claim of each section in the first sentence. Avoid content buried in JavaScript that crawlers can't read.
Think of it this way: if an AI had to summarize your page in one sentence per section, could it? If not, neither can the model — and you're leaving citations on the table.
Category Ownership
Defining your category
The best AI visibility play is owning a category in the model's understanding. This means publishing content that comprehensively answers the questions buyers ask about your category — not just your product.
Write the definitive guide to your category. Define the problem better than anyone else. Establish the criteria buyers should use when evaluating options. AI engines cite the most comprehensive, authoritative sources. Be one.
Comparison content that works
Comparison queries are the highest-intent prompts in AI search. When someone asks "Attio vs HubSpot", they're close to buying. AI engines cite sources that directly compare the two — and give clear, useful answers.
Create comparison pages for every major competitor in your category. Be honest and specific. Explain who each tool is best for. AI engines don't cite marketing copy — they cite content that helps buyers make a decision.
Thought leadership that sticks
Thought leadership creates citation surface area. When you publish a well-researched piece that gets cited in other articles, shared in communities, and referenced in discussions — each of those citations adds to your AI visibility footprint.
Focus on original research, strong opinions, and specific insights that other people want to link to. Generic content doesn't compound. Distinctive content does.
Distribution That Compounds
The third-party mention flywheel
One piece of content published on your own site adds one data point. One mention in a trusted external source adds a data point with multiplied authority weight. And when that external source itself gets cited widely, your mention compounds.
This is the third-party flywheel: earn mentions in trusted sources → those sources get cited → your brand association strengthens in AI models → you get cited more → repeat.
Community presence
AI models were trained on Reddit, Hacker News, indie community forums, and countless niche communities. Being present in those conversations — with genuinely helpful answers, not promotional posts — builds the kind of organic mention density that no paid campaign can replicate.
Find the three communities where your buyers talk about your category. Show up consistently. Answer questions. Over time, your brand becomes part of the community's vocabulary — and the model's.
Earned media over paid
Paid content and advertising don't contribute to AI visibility. Media coverage, editorial mentions, analyst citations, and earned placements do.
For most B2B brands, the highest-leverage PR isn't a press release — it's getting your product mentioned in the tools section of a well-read newsletter, or included in a category round-up by a trusted analyst. These are the sources AI models have learned to weight heavily.
Ready to apply what you learned?
Start tracking your AI visibility →