In deeptech communication, being visible on Google has become a necessary but insufficient condition: you must now be understood by systems which, increasingly, do the research
In recent months, a new category of uses has emerged in the practices of B2B decision-makers: querying LLMs like ChatGPT, Gemini or Perplexity to obtain recommendations on a company or a solution. These systems navigate, synthesize, and compare from sources they have selected. In other words, before a CTO or Director of Innovation lands on your site, an AI agent may have already read your content, assessed your positioning and formed a first impression of your credibility. Or not, depending on the quality of what you publish.
What AI agents look for and what they don’t know
AI agents do not work like a traditional search engine. They don’t just scan keywords and rank pages by popularity. They read, literally: they analyze the structure of an argument, evaluate the coherence of a speech, identify whether a source is capable of answering a specific question with a sufficient level of precision. What interests them is the clarity of the reasoning, the information density and the perceived reliability of the author.
For deeptech companies, this is a fundamental transformation. Until now, the main weakness of their marketing communication strategy was to be technocentric: precise, rigorous content, but constructed for scientific peers rather than for non-specialist decision-makers. This translation deficit penalized human visibility. It will now also penalize algorithmic visibility. Because AI agents, like decision-makers, seek to understand what a technology actually changes, not how it works in detail.
Deeptech communication facing a new filter
In my daily work alongside technology startups and industrial companies, I observe a strong resistance to simplifying technical discourse. This resistance is legitimate, precision is a fundamental value in these sectors. But it produces content that neither investors, nor clients, nor now AI agents can use effectively.
The paradox is that the deeptechs which have the most to gain from this evolution are precisely those which communicate the least well. A startup whose content is structured around a clear problem, explicit business value, and verifiable proof of credibility will be selected by an AI agent as a relevant source. A startup whose site accumulates technical specifications without a conductive wire will be ignored, no matter how revolutionary its technology.
Besides, why producing more content doesn’t make your innovation more visible ? Because the volume does not compensate for the absence of structured discourse. This truth applies to humans. It goes doubly for AI agents, who have neither the patience nor the kindness of a motivated reader.
What this actually changes for the deeptech communication strategy
The first implication is editorial. Each content published as part of a deeptech communication strategy must now answer an explicit question, with a clear answer and a readable structure. Fuzzy, general or purely descriptive content will no longer pass any filter, either human or algorithmic.
The second implication is structural. AI agents favor sources that demonstrate consistent expertise over time. Sporadic, opportunistic speaking out, without an identifiable editorial line, will be perceived as unreliable. This requires investing in a regular, thematically coherent presence, not for volume, but for accumulated credibility.
The third implication, and perhaps the most counterintuitive, is that the quality of speech becomes a commercial selection criterion even before the first human contact. In a B2B deeptech sales cycle that lasts on average six to eighteen months, the moment when an AI agent evaluates your content can precede by several weeks the moment when a decision-maker consults your site directly. This invisible filter is already active. The question is not whether we should prepare for it, but whether we still have time to do so.
The deeptech companies that get ahead on this subject will not be the ones that produce the most optimized content. They will be those who will have understood that deeptech communication now requires a structured and differentiating discourse, a condition of visibility as much as a condition of conviction.
