LSI keywords remain one of the most persistent misconceptions in SEO. The term shows up in keyword research guides, agency service pages, and SEO tool dashboards, even though Google has made clear it does not use this technology.

The confusion is understandable. The concept behind the term, using related terms to help search engines understand content, is sound. The label is wrong, and the distinction matters because it leads teams to optimize for a mechanism Google has not used.

What LSI Actually Is

Latent Semantic Indexing is a real mathematical technique, but it was never designed for web search at the scale Google operates.

The Original Technology

LSI was developed in the late 1980s as a method for analyzing relationships between documents and the terms they contain. The technique uses a mathematical process called singular value decomposition to identify patterns in how words appear together across a collection of documents.

The technology works well for small, static document collections. A corporate intranet with a few thousand documents is a reasonable use case. The entire indexed web, which runs to hundreds of billions of pages, is not. LSI was never built to handle collections of that size, and Google has never confirmed using it as a ranking signal.

What Google Actually Uses

Google processes semantic relationships through entirely different systems. 

• RankBrain uses machine learning to interpret queries the search engine has never seen before and connect them to relevant results. 

• BERT processes natural language bidirectionally, meaning it understands context from both directions in a sentence rather than reading left to right. 

• MUM is multimodal and multilingual, capable of understanding information across text, images, and languages simultaneously.

These systems use much more advanced approaches to understanding language and context than traditional latent semantic indexing. 

Why the SEO Industry Still Uses the Term

If Google does not use LSI, why does the term persist? Three reasons explain it.

Google Has Addressed This Directly

Google's John Mueller stated plainly that "there's no such thing as LSI keywords" and that anyone saying otherwise is mistaken. That statement came directly from Google's Search Advocate, the person whose role is to communicate how Google Search works to the webmaster community.

Despite that, the term continued to circulate. SEO tool providers had already built features around "LSI keyword" suggestions. Training courses had already published modules on LSI optimization. Removing the term meant acknowledging that a significant part of the established curriculum was wrong.

The Concept Is Useful, Even if the Label Is Wrong

What most SEO practitioners mean when they use the term is semantically related terms. Words and phrases that are topically connected to the primary keyword. When someone targets "running shoes," related terms like "cushioning," "gait analysis," "pronation," and "trail running" help search engines understand what the page is about.

That concept is valid. Google's systems do use semantic relationships to evaluate content quality and relevance. The error is attributing that process to a specific 1980s technology that Google does not run. The accurate term is semantic keywords, and the distinction matters because it points to the right optimization approach.

Tool Dashboards Keep the Term Alive

Several SEO platforms still label their related-keyword features as "LSI suggestions" or similar. As long as the tools use the term, practitioners will search for it. The search volume for the term continues to hold precisely because the ecosystem has not updated its language.

What to Do Instead of Chasing LSI Keywords

The practical advice has not changed, even though the terminology should. Building topical depth with semantically related terms is still a core part of effective ​content production.

Write for Topical Completeness

Cover the full scope of a topic rather than repeating a single keyword. If your page targets "email marketing strategy," it should naturally include terms like "open rates," "segmentation," "A/B testing," and "deliverability," not because an LSI tool suggested them, but because a complete treatment of the topic requires them.

Use Google's Own Signals for Keyword Intelligence

Google's "People Also Ask" boxes, related searches at the bottom of results pages, and autocomplete suggestions are more reliable sources of keyword intelligence than any third-party LSI tool. These features reflect what Google's actual systems consider related to a query.

Think in Entities, Not Keywords

Google's Knowledge Graph helps Google understand entities, the people, places, things, and concepts that a page discusses. A page about "Apple" that mentions "iPhone," "Tim Cook," and "Cupertino" is understood differently from a page about "Apple" that mentions "orchard," "harvest," and "cider." This entity-level understanding is what replaced the keyword co-occurrence model that LSI was built on.

The Bottom Line

LSI keywords are not a Google ranking factor, but the idea behind them still points to something important: strong content covers a topic naturally and comprehensively rather than forcing the same keyword into every section. 

If you want that approach to work across both traditional and AI search, a solid SEO foundation paired with a GEO strategy gives you a stronger foundation for both. Talk to an Expert to see how Passionfruit can help bring the two together.

Frequently Asked Questions

What Are LSI Keywords?

LSI stands for Latent Semantic Indexing, a 1980s text analysis technique. In SEO, the term is used loosely to mean semantically related words. Google does not use LSI technology, and the accurate term for related terms that help search engines understand content is semantic keywords.

Does Google Use LSI Keywords?

No. Google has stated directly that "there's no such thing as LSI keywords." Google uses machine learning systems like RankBrain, BERT, and MUM to process semantic relationships, none of which rely on latent semantic indexing.

What Is the Difference Between LSI Keywords and Semantic Keywords?

LSI keywords refer to a specific 1980s technology that Google does not use. Semantic keywords are topically related terms that help search engines understand content meaning. The practical optimization is the same, but the terminology and the underlying mechanism are different.

Should I Still Use Related Keywords in My Content?

Yes. Topical completeness remains important for both SEO and AI search. Cover the full scope of a subject using naturally related terms. Use Google's own features, like People Also Ask and related searches, as your source for relevant terms rather than third-party LSI tools.

Do LSI Keywords Help With AI Search?

The concept of topical depth helps with AI citation, but the LSI label is misleading. AI engines retrieve content based on semantic understanding, not keyword co-occurrence patterns. Pages with genuine topical completeness perform better across both traditional and AI search surfaces.

Are LSI Keyword Tools Worth Using?

The tools themselves can surface useful related terms, regardless of the label they use. Treat any "LSI keyword" suggestion as a starting point, not a ranking formula. Cross-reference suggestions against Google's own related searches and People Also Ask features for validation.