Recently, we had a project at the agency that showed very clearly that the information environment has changed much more than many people assume. We were preparing a strategic review for a large company with a wide regional infrastructure, a business where competition is high and the client's decision is made quickly. As part of the analysis, we checked not only the classic competitive environment, but also how these players look in the responses of ChatGPT, Claude and Gemini. It was an additional experiment, but the result turned out to be significant: the models confidently “highlighted" companies that are not necessarily leaders in terms of scale. They were united by another thing, the most understandable, consistent and structured information trail. The models chose those who best explained themselves to the world.
This conclusion unexpectedly resonated with my recent everyday experience. A couple of weeks ago, I needed a cake for a family celebration and I decided to check out what the AI would offer. The model confidently recommended a certain local brand, not because she "understands taste," but because its website was one of the most structured: detailed descriptions, honest photos, clear order terms and logical navigation. AI took this as a sign of transparency and reliability. And I realized that the model is not recommending the best product, but the one with the best information architecture around.
These two cases, from the professional environment and from everyday life confirm one idea: artificial intelligence has become the main intermediary between a brand and a person. We are increasingly turning not to a search engine, but to AI. And LLM models don't just search for data, they form an opinion. If there is little information about the company or it is chaotic, the model completes the picture itself: by analogy with competitors, outdated texts, emotional comments. This creates a brand version that the business itself may not recognize, but it becomes the first impression.
Content in this new reality has ceased to be a marketing activity. It has become training data. Every product explanation, every interview, analytical column, comment, or video are all meanings from which AI builds an image of the company. Moreover, video content creates the densest "semantic shadow": subtitles, transcriptions, discussions, reposts, retellings. One video clip can give a model more anchor points than dozens of text publications.
The emotional noise of the audience also affects, but only where the company is absent as a source of meaning. If a brand regularly explains its decisions, shows processes, and reacts to the market, the model is based on this data. Algorithms always choose what looks stable, consistent, and validated.
Therefore, the task of business today is not just to publish, but to build a stable information architecture around itself. These are not one-time posts, but a holistic “reputation layer”: explained products, described processes, company position, regular communication. This is a new discipline – reputation management in the age of AI. It requires an understanding of the logic of models, consistency, and the ability to turn the company's experience into data that is easily and correctly interpreted by algorithms.
Some businesses already have such competencies internally. For others, it is more effective to work with external specialists who are able to build an AI-understandable reputational contour. Not for the sake of “content for content's sake,” but for artificial intelligence, the first interlocutor of a modern client, to tell about the company the way it really deserves it. And in an environment where AI forms user solutions faster than strategies can change, this becomes a competitive factor.
Olga Altfater, CEO of Remark Agency
This conclusion unexpectedly resonated with my recent everyday experience. A couple of weeks ago, I needed a cake for a family celebration and I decided to check out what the AI would offer. The model confidently recommended a certain local brand, not because she "understands taste," but because its website was one of the most structured: detailed descriptions, honest photos, clear order terms and logical navigation. AI took this as a sign of transparency and reliability. And I realized that the model is not recommending the best product, but the one with the best information architecture around.
These two cases, from the professional environment and from everyday life confirm one idea: artificial intelligence has become the main intermediary between a brand and a person. We are increasingly turning not to a search engine, but to AI. And LLM models don't just search for data, they form an opinion. If there is little information about the company or it is chaotic, the model completes the picture itself: by analogy with competitors, outdated texts, emotional comments. This creates a brand version that the business itself may not recognize, but it becomes the first impression.
Content in this new reality has ceased to be a marketing activity. It has become training data. Every product explanation, every interview, analytical column, comment, or video are all meanings from which AI builds an image of the company. Moreover, video content creates the densest "semantic shadow": subtitles, transcriptions, discussions, reposts, retellings. One video clip can give a model more anchor points than dozens of text publications.
The emotional noise of the audience also affects, but only where the company is absent as a source of meaning. If a brand regularly explains its decisions, shows processes, and reacts to the market, the model is based on this data. Algorithms always choose what looks stable, consistent, and validated.
Therefore, the task of business today is not just to publish, but to build a stable information architecture around itself. These are not one-time posts, but a holistic “reputation layer”: explained products, described processes, company position, regular communication. This is a new discipline – reputation management in the age of AI. It requires an understanding of the logic of models, consistency, and the ability to turn the company's experience into data that is easily and correctly interpreted by algorithms.
Some businesses already have such competencies internally. For others, it is more effective to work with external specialists who are able to build an AI-understandable reputational contour. Not for the sake of “content for content's sake,” but for artificial intelligence, the first interlocutor of a modern client, to tell about the company the way it really deserves it. And in an environment where AI forms user solutions faster than strategies can change, this becomes a competitive factor.
Olga Altfater, CEO of Remark Agency