AI Overviews vs Featured Snippets: What Changed and What to Optimize Now

For a decade, the position-zero featured snippet was the most coveted slot in search. In 2025, Google quietly replaced featured snippets on ~70% of informational queries with AI Overviews — a fundamentally different surface with different optimization rules. If your AEO playbook still reads like featured-snippet advice from 2022, you're optimizing for the wrong target.

Table of contents

1. What actually replaced featured snippets · 2. The 5 differences that matter for optimization · 3. Page structure: what changed · 4. Schema: what's now mandatory · 5. Multi-source citation: the new game · 6. The migration audit (1 hour) · 7. FAQ

What actually replaced featured snippets?

AI Overviews replaced featured snippets on most informational queries beginning May 2024 and accelerating through 2025. According to Google Search Central announcements, AI Overviews now appear on roughly half of US queries and a growing share globally. Unlike a featured snippet (which surfaced one source verbatim), an AI Overview synthesizes 3–8 sources into a generated answer with inline citation links — meaning multiple brands can appear in one result.

The 5 differences that matter for optimization

1. Single-source vs multi-source: snippets pick one winner; AI Overviews cite 3–8. 2. Verbatim vs synthesized: snippets quote your text; AI Overviews paraphrase. 3. CTR pattern: snippets drove 8–15% CTR; AI Overview citations drive 1–4%. 4. Volatility: snippet winners were sticky; AI Overview citations rotate weekly. 5. Optimization unit: snippets reward one perfect paragraph; AI Overviews reward whole-page entity strength + multiple quotable blocks. **The strategic shift: stop optimizing for one paragraph; optimize for being one of the synthesized sources.**

Page structure: what changed

Featured-snippet optimization rewarded a single 40–55 word answer immediately under the H2 matching the query. AI Overview optimization rewards multiple 40–80 word answer blocks throughout the page (one per question-led H2), an FAQ section with at least 3 question/answer pairs, a TL;DR or summary near the top, and consistent internal entity references (your brand name in every H2 section). One paragraph isn't enough anymore.

Schema: what's now mandatory

Featured snippets worked with or without schema — clean HTML was sufficient. AI Overviews favor pages with valid Article + FAQPage schema, dateModified within 6 months, and Organization schema with sameAs links. **Pages with no schema still occasionally get cited, but at roughly 1/3 the rate of equivalent pages with valid schema** based on observational audits.

Multi-source citation: the new game

Because AI Overviews cite 3–8 sources, you no longer need to be the single best page — you need to be one of the most quotable, fresh, structurally clean pages in the candidate pool. This lowers the bar to entry but raises the bar on consistency. A site that ships 50 well-structured pages will out-cite a site with 5 perfect pages and 200 thin ones.

The migration audit (1 hour)

On your top 20 organic pages: (a) confirm at least one 40–80 word direct answer block under each H2, (b) add FAQPage schema with 3+ Q/A pairs, (c) ensure dateModified is within 6 months, (d) add or refresh Organization schema with sameAs, (e) re-validate in Google's Rich Results Test. This 5-step audit recovers most pages that were AI Overview candidates but were being skipped due to structure or schema.

Frequently Asked Questions

Are featured snippets completely gone?

No — they still appear on ~30% of informational queries (mostly definition and how-to queries where AI Overviews aren't triggered). Continue to optimize for both surfaces; the techniques overlap heavily.

Did clicks really drop that much?

On informational queries with AI Overviews, organic CTR dropped 30–60% in published studies. The trade-off is brand exposure inside the AI answer (similar to brand impressions in search ads). Pure-traffic teams are losing; brand-aware teams are adapting.

Will Bing/ChatGPT/Perplexity converge on the same model?

They've already converged structurally — synthesized multi-source answers with inline citation. Differences are in source-weighting and freshness. The optimization playbook for one largely transfers to the others.

Should I add schema to legacy content?

Yes — schema is the highest-ROI retrofit on existing pages. A weekend pass adding Article + FAQPage schema to your top 50 pages typically lifts AI Overview citation rate noticeably within 30 days.

How do I track AI Overview citations?

Tools like Profound, Otterly, AthenaHQ, and SE Ranking now track AI Overview presence and citation. Manual sampling on a defined prompt set re-run weekly works for smaller programs. GA4 traffic from chatgpt.com / perplexity.ai / gemini.google.com gives downstream signal.