Pull up whatever AI tool your team used to create an SEO program. Now picture your competitor doing exactly the same thing. Because they probably did.
AI is a genuinely useful research tool. The problem is that it draws from the same public web dataset every time, and for everyone. When you build your strategy from that output alone, you get back the same recommendations your competitors are getting. The tactics look actionable on paper. They just happen to be the same tactics everyone else is using.
Lisa Ainza, our Senior Director of Organic Search, and I talked through this in our most recent Coffee Chat because it keeps coming up in conversations with marketing leaders who are trying to figure out where AI actually fits in their organic search programs.
AI Is a Research Assistant. It's Not a Strategist.
I'll say what I tell clients: AI can accelerate your work. It can surface keyword clusters, compress research that used to take a week into an afternoon, and flag content gaps faster than any team can manually. That, nobody can deny.
AI can't account for internal resource allocation, budget limitations, development constraints, specific business goals or the nuances between a good and a bad customer. AI knows the web, the here and now. It won’t be able to know your business or your consumer as well as you do. The model delivers a highly articulate template of the industry standard. But, in order to take share in this new AI era, you need to differentiate yourself.
"If you are asking AI for strategies, we’ve seen that AI repeats itself. Your competitors are probably getting the exact same recommendations because they are so high-level, the same tactics." Lisa Ainza, Senior Director of Organic Search, LQ Digital
For your company to stand out and take market share, an AI tool trained on what everyone else has already done cannot tell you how to beat them.
The hidden risk of AI: competitor homogenization
The appeal of a 90-day content plan generated in 45 seconds makes sense when budgets are tight. The problem is that generic plans and content won’t take you where you want to go. They can even work against your site's long-term organic health.
Search engines have gotten very good at identifying the difference between content built to serve a reader and content built to check a box. And what we're seeing in practice: teams solely relying on AI tend to land on the same low-value plays. FAQ pages stuffed with schema markup, generic listicles targeting head terms, content that covers a topic without actually saying anything about it.
Moving fast in the wrong direction is still moving in the wrong direction.
Hallucinations are a Real Problem
Moreover, as AI-driven answer engines become the primary interface for information, the risk is not only about ranking, it's also about representation.
AI systems will fill in the gaps about your brand when they can't find clear, consistent information. If your brand narrative comes from a set of generic instructions without a strong brand identity, you are handing that control to a system that will make its best guess.
What actually works in this environment is building a layered, consistent brand narrative across your own properties, third-party profiles, local listings, and authoritative external sources. Not because a guideline says to, but because AI systems synthesize from what they can find. If you don't give them something accurate to work from, they'll work with what's there.
This is what Answer Engine Optimization and Generative Engine Optimization actually require. And most marketing leaders are underestimating how urgent it is.
The Part That Matters
Access to information is not the same as strategy. A tool that generates 300 content ideas in 30 seconds has given you access to information. Strategy is knowing which three of those ideas will move your business, in what order, given your resources, your competitive position, and where you're actually trying to go.
The real power comes from harnessing the tool. It comes from layering smart AI with seasoned practitioners who've run these programs at scale and know how to connect search performance to business outcomes that a CFO will recognize.
Lisa and I went deeper on all of this, including what teams should actually be doing differently right now, in our full Coffee Chat. If you're a marketing leader trying to separate AI signal from AI noise in your search programs, it's worth 20 minutes.
Watch the full Coffee Chat here →
