I still hear these two treated as basically the same thing, "get featured snippets, now called AI Overviews," which understates a real, mechanical difference worth understanding properly.
The Core Mechanical Difference
A featured snippet is, at its core, a single excerpt lifted from a single page, Google identifies one specific passage that directly answers a query and displays it, attributed to that one source. It's been part of Google's results for years, well before generative AI search existed, and it works through a relatively simple extraction process: find the best single existing answer already on the web and surface it prominently.
An AI Overview works differently. It's a generated response, synthesized from multiple sources at once, often through the fan-out retrieval process, not lifted verbatim from any single page. The output is new text, written by the model, informed by several sources, with citations pointing to where different pieces of that synthesis came from. That's a meaningfully different task than finding and displaying one existing excerpt.
Why This Distinction Actually Matters for Strategy
What does GEO stand for in the context of AI search optimization?
Because a featured snippet rewards being the single best, cleanest existing answer to a specific query, optimizing for it is closer to classic on-page SEO with an emphasis on concise, directly-extractable phrasing. An AI Overview rewards being one of several good sources the system can pull from and synthesize together, which means comprehensive topical coverage matters more than being the single, definitive answer to one narrow query, since your content might contribute one piece of a broader synthesized answer rather than being the entire answer itself.
This is part of why answer-first content structure helps with both, a clean, direct answer up top is extractable as a snippet and easily incorporated into a synthesized AI Overview, but the AI Overview additionally rewards depth and comprehensive coverage across a topic in a way snippet optimization alone never specifically required.
Featured Snippets vs. AI Overviews: What Changed and What Didn't
Do Featured Snippets Still Matter, Given AI Overviews Exist
Yes, and I want to be direct about this since some content treats featured snippets as obsolete. They still appear independently of AI Overviews for many queries, and the content structure that earns a snippet, a concise, directly-extractable answer, is largely the same structure that helps AI Overview extraction too. There's real overlap in what you build for both, which means optimizing for one doesn't require abandoning the other, they're complementary targets sharing a similar underlying content discipline, not competing priorities.
The Practical Difference in How You'd Measure Success
How has AI Overview affected your or clients' organic traffic quality?
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Tracking a featured snippet is relatively straightforward, you either hold position zero for a given query or you don't, a binary, trackable state. Tracking AI Overview citation is messier, since your content might be one of several cited sources, contributing partially to a synthesized answer rather than being the whole answer, which is part of why how AI Overviews choose what to cite requires understanding a broader, less binary set of signals than snippet optimization alone ever did.