What happened
Semrush has released a comprehensive study focusing on the impact of AI-powered search engines (such as Google AI Overviews and Perplexity) on the manufacturing sector. The research analyzed which industrial brands are most frequently mentioned by Large Language Models (LLMs) and whether these mentions translate into actual web visibility. The findings reveal a surprising reality: while many manufacturing brands are cited as information sources, this does not always drive a direct flow of users to their websites, fundamentally changing how SEO success is measured in the industrial space.
Technology context
Unlike traditional search, where algorithms index web pages and display them as a list, AI Search (or Generative Engine Optimization - GEO) uses generative models to synthesize complex answers. Instead of directing a user to a specific page, the AI extracts information, processes it, and presents it directly. Citations (the footnotes or references within the generated text) are the way AI validates its sources, but user behavior is shifting from "click for details" to "direct information consumption."
Why it matters
For manufacturing companies, where sales cycles are long and based on rigorous technical specifications, appearing in AI-generated responses is vital for brand authority. However, the Semrush study warns that classic SEO strategies focused solely on keywords are no longer sufficient. If the AI provides a complete answer without the user ever visiting the site (the "zero-click search" phenomenon), companies must redefine their KPIs, moving from traffic volume to "share of model voice."
Key terms explained
- AI Overviews (SGE): A Google feature that uses artificial intelligence to provide a generative summary at the top of search results.
- GEO (Generative Engine Optimization): The process of optimizing content to increase the likelihood of it being used and cited by generative search engines.
- Zero-Click Search: A search engine query that ends without the user clicking on any result because the information was found directly on the results page.
- LLM (Large Language Model): AI systems trained on vast amounts of data capable of understanding and generating human-like text, which power AI search tools.
Impact
In the short term, manufacturing companies will likely see a decline in informational organic traffic but an increase in the relevance of the visitors who do reach their site. In the medium term, brands that fail to become "trusted sources" for LLMs risk becoming invisible in new search interfaces, regardless of their ranking in traditional organic results.
What's next
We anticipate a transition toward highly specialized content and much more complex structured data (Schema Markup) to help AI understand the technical specifications of industrial products. Digital marketing in manufacturing will focus less on "capturing the click" and more on "indirectly training models" through digital PR and high-quality technical documentation made publicly available.
Sources: SEMrush Blog, Manufacturing SEO Analysis 2024-2025.
Disclaimer: Educational analysis generated with AI and editorially reviewed.