6 SEO Strategies to Rethink for AI Search

Yes, SEO and AEO share common ground, but they are not interchangeable. Relying solely on your established search optimization playbook will limit your success in the evolving world of AI search visibility.

What, then, requires a shift in strategy?

Instead of rehashing content structure adjustments for AI, I will concentrate on three priorities that have gained significance and three that have lost their edge in the age of generative search.

3 SEO Priorities to Double Down On

Establish Brand Authority and Strong Entities

Before an AI system will cite your brand, it must first know you exist and understand what you represent. Entity recognition has become foundational for AI visibility in a way it never was for traditional search, even though Google’s Knowledge Graph has long rewarded brands using this method. Large language model (LLM) training data favors brands with a consistent, cross-platform presence.

For our clients, we now prioritize ensuring brand information is uniform across Wikipedia, LinkedIn, Crunchbase, industry directories, and any other source an LLM might use to gather entity data. Furthermore, PR and SEO/AEO teams must collaborate more closely because earned media mentions now function as critical entity-building signals.

E-E-A-T was already steering us in this direction, but building author entities is now more important than ever. Bylined experts with their own credible web presence significantly boost the authority of the content they produce. When we invest in entity building, we consistently see faster AI citation gains when we publish strong content, because the necessary infrastructure is already in place.

Build Topical Depth with Content Clusters

AI systems prefer sources that demonstrate comprehensive authority on a subject, not just individual pages that rank for isolated keywords. A thin content footprint is far more exposed in AI search than it was in traditional search. This means keyword-by-keyword content planning must 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 critical because it signals topical relationships between pieces for LLM ingestion. Regular content audits should also shift focus from merely identifying underperforming pages to uncovering gaps in topic coverage. When we go deep on a niche, we often 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 any sales conversation begins. We also receive more feedback that buyers are seeing our clients in LLMs while researching before making a purchase.

Earn Unlinked Brand Mentions and Community Presence

LLMs are trained on the broader web, not just pages with backlinks. A mention of your brand on Reddit, Quora, a niche forum, or an industry community carries significant weight, even without a link. AI systems pattern-match what the web says about you across many sources, not just what ranks in Google. Owned content alone cannot 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 is 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 is 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, as 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 number one for a broad head term often means you have invested significant effort in 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 does not.

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 is not 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 cannot 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 will not 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 Click-Through Rate on Zero-Click Queries

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.

The Payoff Isn’t Always More Traffic

There are certainly more shifts to consider, but these are the first ones I would 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 is the tradeoff AI search increasingly rewards.