Yes, SEO and AEO have plenty of overlap, but they aren’t the same. Sticking with your tried-and-true SEO approach won’t get you as far in AI search visibility.
So what needs to change?
Rather than revisit content structure for AI search, I’ll focus on three priorities that matter more in AI search and three that matter less.
3 SEO priorities to emphasize more
Establish brand authority and strong entities
AI systems need to “know” your brand exists and what it stands for before they’ll cite you. Entity recognition is foundational to AI visibility in a way it never was for traditional search, although Google’s Knowledge Graph has long highlighted brands using this approach. LLM training data rewards brands with a consistent, cross-platform presence.
For our agency’s clients, we focus more on ensuring brand information is consistent across Wikipedia, LinkedIn, Crunchbase, industry directories, and anywhere else an LLM might pull entity data.
PR and SEO/AEO teams also need to work more closely together because earned media mentions are now entity-building signals.
E-E-A-T was already pointing in this direction, but building author entities matters even more now. Bylined experts with their own credible web presence add authority to the content they produce.
When we can invest in entity building, we tend to see faster AI citation gains when we produce strong content because the infrastructure is already in place.
See where your brand appears in AI search, where competitors are winning, and what it takes to become the answer AI recommends.
Build topical depth with content clusters
AI systems favor sources that demonstrate comprehensive authority on a topic, not just individual pages that rank for individual keywords. A thin content footprint is much more exposed in AI search than it was in traditional search.
Keyword-by-keyword content planning needs to give way to topic ownership planning. Stop asking, “What do we rank for?” and start asking, “What topics do we want AI systems to associate us with?”
Internal linking becomes more important because it signals topical relationships between pieces for LLM ingestion. Content audits should also become a regular exercise to identify gaps in topic coverage, not just underperforming pages.
When we can go deep on a niche, we tend to see content cited across multiple related queries. One strong content cluster can generate broad AI visibility.
Owning a topic cluster around the problem a client’s product solves positions them as the authoritative resource before the sales conversation even starts. We also get more feedback that buyers are seeing them in LLMs while researching before making a purchase.
Earn unlinked brand mentions and community presence
LLMs are trained on the broader web, beyond pages with backlinks. A mention of your brand on Reddit, Quora, a niche forum, or an industry community carries weight even without a link.
AI systems pattern-match what the web says about you across many sources, not only what ranks in Google. Owned content alone can’t manufacture that signal.
Trusted third-party communities like Reddit carry particular weight because LLMs have been heavily trained on them and often treat their content as authentic user sentiment.
Community participation and digital PR are now SEO-adjacent priorities. Getting your brand mentioned in the right places matters, whether a link is attached.
Monitoring unlinked brand mentions is becoming as important as tracking backlinks. Tools like Brandwatch and Mention, along with manual Reddit and Quora monitoring, can surface where your brand is and isn’t appearing organically.
Talk with your team less about who’s linking to you and more about where your brand is being discussed, and whether those conversations are positive and accurate.
Brands with an active presence in relevant communities tend to surface more naturally in AI answers to conversational, recommendation-style queries, such as “What does Reddit think about X?” or “What’s the best Y according to users?”
For challenger brands trying to break into a category, earned community mentions can build AI-visible authority faster than traditional link building, which takes time to accumulate.
B2C brands, in particular, benefit from genuine community presence. Consumer AI queries often skew toward social proof and peer recommendations over authoritative publications.
3 SEO priorities to emphasize less
Chasing high-volume keywords with thin content
AI Overviews absorb the click for generic informational queries. Ranking No. 1 for a broad head term increasingly means you’ve put a lot of effort into attracting traffic that never arrives.
Volume alone is no longer a proxy for opportunity. A query with 50,000 monthly searches that triggers an AI Overview may deliver less traffic than a query with 2,000 searches that doesn’t.
Craft specific, authoritative content that answers a narrower question better than anything else available. Focus on queries where the searcher needs to take action, make a comparison, or access something only your site provides. Those are harder for AI to fully resolve.
The traffic potential of a keyword is no longer the primary metric. First ask whether someone will still need to click through after AI answers the query. If the answer is no, the opportunity isn’t what it used to be.
Pursuing exact-match and manipulative link building
Low-quality link volume does nothing for AI citation likelihood. LLMs weight the authority and relevance of citing sources, not raw link counts. The publications that matter for AI citation are those with genuine editorial standards, which can’t be gamed the way link networks can.
Focus on earning coverage and links from the outlets AI systems actually draw from, such as trade publications, respected blogs, and academic-adjacent sources. Build content worth referencing instead of relying on outreach designed to extract a link.
A hundred low-quality links won’t get you cited in ChatGPT. Five links from publications your target audience actually reads might. The metric that matters is source authority, not link volume.
Optimizing for CTR on standard blue links
A growing share of informational queries are resolved without a click. As a result, optimizing titles and meta descriptions for CTR on queries dominated by AI Overviews offers diminishing returns. Time and resources spent on micro-optimizing CTR for zero-click queries could be better spent earning the citation within the AI answer.
Aim to become the cited source within the AI answer rather than the blue link below it. For queries where clicks still happen, focus on transactional and navigational intent because those are more resistant to AI resolution.
CTR optimization assumes someone is choosing between results. For a growing share of queries, that choice is made before the blue links appear. The game has moved up the page.
Track your visibility across AI search, uncover missed opportunities, and grow your presence where customers are asking questions.
The payoff isn’t always more traffic
There are certainly more shifts to consider, but these are the first ones I’d make. You may lose some volume in traditional SEO metrics like impressions and clicks, but that should have little downstream effect on the metrics that matter most, including conversions, pipeline, and revenue. That’s the tradeoff AI search increasingly rewards.
