Anja Leipold
Marketing & Industry Awareness Committee Member
MENZEL Elektromotoren GmbH
Hennigsdorf, Germany
Imagine the following situation: A maintenance manager faces an unexpected shutdown of a high-power industrial motor. Until recently, his next step was obvious: he would type queries like “500 kW electric motor repair” or “fast industrial motor service” into Google.
Today, he asks an AI search: “Which electric motor repair company is reliable and recommended for high-performance industrial drives?” What comes back is no longer a ranked list of search results. It is a recommendation. And with it, a fundamental shift in how companies are discovered and chosen has begun.
Visibility is No Longer a Ranking Problem
For decades, digital visibility meant mastering search engine optimization: keywords, backlinks, page authority, rankings. These mechanics still matter. But they no longer tell the whole story.
AI-driven search systems such as ChatGPT, Perplexity and Google’s AI-powered answers operate by new logic. The decisive question is no longer where a website ranks, but whether a company is considered credible, relevant and recommendable by AI itself. This emerging discipline is often described as Generative Engine Optimization (GEO).
How AI Decides Which Brands to Recommend
Current research shows that AI systems favor brands with a clear and consistent digital footprint. They evaluate how frequently a company is mentioned online, the professional context of those mentions, and how coherent they are across sources. AI connects this information into an overall picture. The more clearly a brand is associated with specific services, the higher the likelihood that it will appear in AI-generated answers.
For electric motor manufacturers and service providers, this means that good products alone are no longer enough. Their capabilities must be clearly, consistently and transparently linked to the company name across digital channels. If AI cannot clearly understand what a company stands for, it will not recommend it.
Content Beats Promotion
Another critical factor is content. AI systems do not reward marketing language. They prioritize technically sound, well-structured explanations that genuinely clarify complex topics.
This is where industrial companies have a strategic advantage, but unfortunately, they often fail to use it. Vast amounts of practical engineering knowledge remain undocumented or locked away in internal systems. Content that provides depth, structure and real insight is far more likely to be cited, summarized and trusted by AI.
Equally important is format. Clearly organized texts, meaningful headings and structured data formats such as FAQs or how-to guides make it easier for AI systems to correctly interpret content.
Trust is Built Beyond Your Corporate Website
AI trust does not originate solely from a company’s own site. Trade publications, technical journals, knowledge platforms, editorial coverage and professional communities all serve as key reference points. As a result, digital PR and expert visibility beyond owned channels are becoming decisive factors for AI-driven discoverability.
Despite all these changes, one thing remains true: traditional SEO is not disappearing. Technical fundamentals such as page load speed, clean crawling, mobile usability, internal linking and up-to-date content remain essential. Without them, AI systems often cannot properly capture or evaluate content in the first place.
Conclusion: What AI Recommends Will Define Tomorrow’s Winners
What is helpful, understandable and credible for people is equally so for AI. What AI understands and trusts is what it recommends. Everything else fades from view.
For you and your company, this means that a clear corporate profile, high-quality and well-structured technical content, and visibility on trusted third-party platforms are no longer optional marketing tactics. They are the price of admission to future visibility.
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