AI Overviews are changing what “winning” in search looks like. Instead of a simple race to the top ten blue links, Google is increasingly answering questions directly on the results page, compressing research, comparing options, and citing a handful of sources.
That shift doesn’t mean SEO is dead. It means SEO needs a new operating model: keep foundational best practices, but redesign strategy, content, and measurement for an environment where rankings can stay steady while clicks decline, and where being cited can matter as much as being #1.
1) Google’s message: there is no “special optimization” for AI Overviews
Google’s official documentation is explicit: there are no additional requirements or “special optimizations” needed to appear in AI Overviews (or AI Mode). If your pages are indexable and eligible for snippets, you can be eligible to support AI Overviews, so the gatekeeping factors remain technical accessibility and quality signals you already manage in standard SEO.
In practice, this means the basics still decide whether you can even be considered: clean crawling and indexing, canonicalization, sound internal linking, accurate titles and meta, and content that aligns to user intent. If you block snippet usage or make content hard to crawl, you reduce the likelihood of being surfaced as a supporting link.
Google also frames AI Overview visibility as a reward for “helpful, reliable, people-first content.” That is a useful constraint for teams tempted to chase shortcuts: your best lever is still clarity, accuracy, and usefulness, not tricks aimed at the AI box.
2) The click reality: AI Overviews correlate with fewer visits even when rankings hold
Multiple datasets point to the same uncomfortable outcome: when AI Overviews show, external clicks tend to drop. Pew Research analyzed March 2025 browsing behavior and found that traditional clicks were lower when an AI summary appeared (8% vs 15%), and clicks on links inside AI Overviews happened about 1% of the time.
Reporting around Pew’s dataset adds scale: it examined 68,879 searches, with about 18% triggering an AI Overview (12,593 instances). SEO industry commentary (including SISTRIX) distilled the core takeaway bluntly: AI Overviews can roughly halve click-through rates.
Ahrefs found a similar directional impact using a large keyword set: the presence of an AI Overview correlated with a 34.5% lower CTR for the #1 result across ~300,000 keywords. Other third-party analyses and publisher-facing coverage have echoed even steeper drops for certain query types and verticals, reinforcing that “rankings stable, clicks down” will become a common pattern as AI boxes sit above classic results.
3) The new north star: rank, but also get selected as a cited source
If AI Overviews reduce overall click opportunity, the most practical goal shift is from “rank #1” to “rank + be referenced.” Seer Interactive’s research highlights this nuance: while queries with AI Overviews saw major CTR declines (organic and paid), sites that were cited within AI Overviews correlated with better CTR outcomes than those that weren’t cited.
Seer reported that being cited aligned with uplift (e.g., organic +35% and paid +91% in their analysis window), even as the presence of AI Overviews dragged aggregate CTR down across the board. The implication is not that citations fully “solve” the click-loss problem, but that citation status can meaningfully change relative performance within an AI-first SERP.
So “rethink SEO for AI overviews” becomes a selection problem: what makes your page a plausible supporting source? You still need relevance and authority, but you also need content that is easy to excerpt, verify, and attribute, so the model can safely quote or cite it.
4) Plan for multi-turn discovery: Gemini 3 and follow-up questions make search session-based
On January 27, 2026, Google announced upgrades that make AI Overviews more conversational: Gemini 3 became the default model, and users can ask follow-up questions directly from the Overview. Industry coverage described the SERP becoming more “chat-like,” reflecting a broader move toward AI-first, dialogue-driven search experiences.
This matters because classic SEO often assumes a single query → single click → single landing page. Multi-turn journeys break that assumption: the user might refine, compare, and narrow their needs within the Overview experience before ever clicking out, if they click out at all.
To compete in that environment, your content strategy should anticipate sequences of questions. Don’t just answer the “” query; build clusters that cover definitions, tradeoffs, steps, troubleshooting, costs, and “best for X” variations, so you remain relevant as the user pivots through follow-ups.
5) Content engineering for citation: write like a source, not just a destination
Citation-friendly pages tend to share traits: they present concrete facts, clear explanations, and unambiguous structure. Think in terms of quotable units, tight definitions, bullet-proof steps, and well-scoped sections that can be excerpted without losing meaning.
Make claims verifiable. Use specific numbers (with context), cite primary sources when possible, and date sensitive statements. When you review products, methods, or policies, be explicit about your evaluation criteria and what changed over time, this helps your page function as a reference rather than a generic summary.
Format also matters. Use descriptive ings, short paragraphs, and lists where appropriate so the key points are easy to parse. This is not “optimizing for the robot” so much as producing a document that is easy for humans, and therefore systems, to extract accurately.
6) Distribution signals: AI Overviews often cite beyond your own domain
As AI Overviews expand, the set of cited domains can be surprisingly diverse. Ahrefs’ coverage of AI Overview growth noted that certain platforms and communities (such as Reddit and Wikipedia) appear frequently, suggesting that Google’s selection behavior may reflect where the web’s consensus, firsthand experiences, or canonical definitions live.
That doesn’t mean you should abandon your site. It means brand presence and content distribution can influence whether you show up in the “universe of sources” the model is comfortable citing. If your niche relies on community validation, participating in reputable forums, maintaining accurate Wikipedia-relevant references where appropriate, and earning mentions in trusted publications can be part of modern SEO.
The strategic adjustment is to treat “authority” as multi-surface. Your goal is not only to publish, but to be referenced across the ecosystem that AI Overviews frequently draw from, without resorting to spammy syndication or low-quality placements.
7) Measurement rethink: stop judging performance by last-click alone
Pew’s finding that AI Overview citation links were clicked about 1% of the time is a warning about KPI design. Even if you earn citations, you may not see a proportional jump in sessions, because the SERP itself is doing more of the job your content used to do.
At the same time, Google leadership has suggested (as quoted in Ahrefs’ reporting) that links within AI Overviews can get higher clickthrough rates, yet independent CTR studies often show overall click suppression when Overviews appear. The reconciliation is that both can be true in different ways: citations may outperform nearby classic results on the same SERP, while the entire SERP sends fewer total clicks than before.
So update reporting to separate: (1) query sets that trigger AI Overviews, (2) whether your brand is cited, and (3) how classic organic CTR changes when the Overview is present. Then expand success metrics to include brand search lift, assisted conversions, newsletter signups, direct traffic trends, and downstream revenue, because visibility and trust may be the primary value even when last-click declines.
8) Operational SEO in the AI Overviews era: fundamentals + governance
Because AI Overview eligibility relies on normal indexing and snippet eligibility, technical hygiene remains a gatekeeper. Ensure important pages are crawlable, not blocked by robots rules or misconfigured noindex, and that canonicalization and rendering issues don’t prevent Google from understanding the main content.
Also prepare for shifting traffic composition. As reported in early 2026 coverage citing Tollbit, AI bots are rising as a share of web traffic, with RAG/indexer bots increasing sharply in late 2025. That raises practical governance questions: how you manage bot access, how you monitor server load, how you attribute content usage, and how you protect premium material while still being discoverable.
Finally, align teams around the new reality: SEO, PR, editorial, and product marketing should coordinate on “source-worthy” content, digital PR that earns credible mentions, and measurement that doesn’t punish teams for macro CTR declines caused by SERP design changes.
Rethinking SEO for AI Overviews isn’t about chasing a new loophole. Google’s own guidance says there’s no special optimization, so the winning play is to deepen the fundamentals, then adapt strategy to how search behavior is changing.
Expect more zero-click journeys, more conversational follow-ups powered by Gemini 3, and more pressure on attribution. The brands that win will be the ones that stay indexable and snippet-eligible, publish content that reads like a reliable source, earn citations across the wider web, and measure success beyond the last click.
