Artificial intelligence is no longer just a buzzword, but a hidden driver of change in consumer behavior. It permeates every click and search query, transforming the way customers make decisions and how brands need to reach them. This article examines the unusual aspects of AI’s impact on consumer choice models and how marketing strategies are being forced to adapt. We avoid platitudes such as “personalization is good” and instead focus on little-studied phenomena: from the disappearance of user anonymity to a new trust in algorithms.

Marketers and business managers will find a fresh perspective on the role of AI: how it destroys the illusion of privacy, becomes a “guru” for customers, changes the logic of brand trust, gives rise to new consumption habits, and blurs the lines between marketing, product, and service.

The end of anonymity: AI and consumer microbehavior

The era when internet users could remain almost anonymous is rapidly fading. Modern AI systems are capable of recognizing and tracking even “unknown” visitors to online resources. For example, some platforms already use device identification to recognize users without a login. As Perry Ellis’ senior marketing director notes, Wunderkind’s Open Graph ID tool allows you to “recognize anonymous visitors by device ID,” giving brands access to detailed audience information from the very first visit. In other words, AI removes the mask of anonymity: even if a customer does not leave explicit data, their digital footprint (device, browser, behavior patterns) reveals their preferences.

What’s more, AI analytics now delves into the micro-behavior of consumers. Every little delay, scroll, or mouse movement can be analyzed. AI records the sequence and context of user actions in real time, providing an unprecedented level of detail in the customer profile. As observers note, marketers now see not only what the customer does, but also when, in what sequence, and under what conditions. This granularity allows for the implementation of targeted personalization strategies that were previously impossible on a large scale.

Unexpected patterns are also emerging. AI can provide counterintuitive insights: for example, a user who spends more time reading reviews is less likely to buy than one who makes a quick decision. For marketers, this is a signal to change their approach – perhaps by simplifying content or giving a “nudge” to those who hesitate too long. Thus, artificial intelligence simultaneously deprives consumers of anonymity and provides marketers with a new microscope for behavior – from general trends to individual nuances.

Generative AI – a new authority for customers

Consumers used to search for answers on Google or trust the recommendations of friends and reputable brands. Now, generative AI is increasingly taking on the role of such a “guru” – for example, a chatbot like ChatGPT or a built-in AI assistant in a search engine. This shift is clearly visible in the behavior of online search users. A study by Bain & Company shows that about 80% of Internet users already get the information they need directly on the results page  –  that is, they don’t click further  –  in at least 40% of their searches. In other words, people are increasingly satisfied with a short AI response without going to brand websites, leading to a 15-25% drop in organic traffic.

In addition, individual AI platforms where users seek advice directly are gaining popularity. Already, 42% of users of large language models (LLMs) turn to them for shopping recommendations. Roughly speaking, instead of Googling “which smartphone to choose” and reading dozens of reviews, consumers can ask a chatbot, which will immediately provide an “authoritative” answer. Such content often sounds confident and professional, so users tend to trust it as expert opinion. Generative AI is quietly “replacing” traditional sources of information – search engines, reviews, even advice from consultants – and is itself becoming a source of influence on choice.

If you want to integrate generative artificial intelligence but don’t know how it works yet, check out Generative Engine Optimization.

However, there is a downside to this trend. AI responses do not reveal the basis for their advice and may contain errors. AI-generated content, although it appears authoritative, lacks transparency regarding its sources and sometimes “hallucinates” facts, making it critical for consumers to verify the information.

This raises the question: have we started to check facts less, trusting AI too much? This is a signal to marketers: even an AI algorithm that has summarized someone’s opinion about your product can shape your brand’s reputation. Therefore, you need to work on your brand’s presence in these new “mouths.”

Trust based on algorithms: the new logic of brand image

Traditionally, trust in a brand was built through product quality, effective communication, and the reviews of others. Now, however, there is often an algorithmic intermediary between the consumer and the brand, and the logic of trust is being rebuilt according to its dictates. Customers increasingly rely on what the algorithm offers them: a news feed, a recommendation system, or a voice assistant. Thus, trust shifts from the brand itself to the platform that showed the brand. If a product is marked “recommended for you” or has a high position in the search results, the consumer subconsciously perceives this as a sign of quality. Marketers point out that the customer journey is increasingly becoming a “story written by an algorithm,” where what the user sees is determined by the machine.

The result is an interesting intertwining of trust. On the one hand, the consumer trusts the recommendation (“my smart assistant recommended this brand to me, so it must be good”). For example, in the field of voice commerce, it has been noticed that if a user asks a smart speaker to order a product, they often agree to the assistant’s first suggestion without even hearing the alternatives. Thus, the algorithm actually decides which brand will be purchased, and the consumer does not object because the credit of trust is given to the assistant.

On the other hand, if the experience fails (poor recommendation, AI error), it undermines both trust in the brand and trust in the technology. This poses a challenge for companies: they need to build their presence and reputation not only in the eyes of people, but also in the “eyes” of algorithms. The brand must be what the algorithm filters as the best option  –  otherwise, it may be bypassed by competitors who better fit the algorithmic criteria.

In addition, the transparency and ethics of algorithms are becoming part of the brand image. If a company uses AI (for example, a chatbot for consultations or recommendations), the honesty of this AI and its ability to explain the recommendation will influence whether customers trust the brand. Research shows that the openness of the algorithm can strengthen trust in both the system and the company that uses it.

Therefore, marketing strategies must take into account that trust is now formed on two levels: at the level of human perception and at the level of algorithmic output. A brand that can win both will have a competitive advantage.

New consumer habits influenced by AI

Interaction with artificial intelligence is giving rise to completely new behavior patterns among customers. Here are just a few notable changes:

  • Delegating choice to AI. Some consumers are beginning to delegate the routine of making choices to technology. Instead of comparing dozens of models themselves, they ask a chatbot, “What’s best for me?”
  • Less verification, more trust. 73% of those who have already used AI in shopping named it as their main source of product information.
  • New ways to find benefits. Consumers are mastering AI tricks for their own purposes. For example, they search for discounts or coupon codes through AI, generate shopping lists, or gift ideas.

38% of consumers have already used generative AI for online shopping, and 52% plan to join within a year. Interaction like with a live interlocutor. Consumers are increasingly interacting with brands through dialogue interfaces, whether it’s a chat on a website, a voice assistant, or a messenger bot.

Customers who are used to the friendly tone of Alexa or Siri expect the same from brand bots. If the experience is positive (the bot really helped), it strengthens loyalty. If not, disappointment is associated with the brand. Thus, AI interfaces are becoming part of the customer experience. We talked about how customers interact with AI agents in the article:

What will happen to marketing in the era of AI agents?

Blurring the lines between marketing, product, and service

The classic boundaries between the departments of “marketing,” “product development,” and “customer service” are increasingly blurring, largely thanks to AI. Personalization algorithms and chatbots work at all stages of the customer journey at once, combining functions that were previously separate.

For example, a modern chatbot can simultaneously act as a salesperson, consultant, and support service. A customer can ask a question to the support service (“how do I return a product?”) and receive not only an answer, but also a personalized recommendation for another product based on their preferences, and make a purchase right in the same chat. In this way, service interaction seamlessly flows into marketing, and marketing flows into sales. Such tools “blur the line between marketing and service,” because the entire interaction is a single seamless experience for the customer.

Moreover, the product itself now often contains built-in marketing. If a mobile app or device has AI functionality that suggests new features or additional products to the user, this is already an element of marketing within the product.

The marketing strategy should cover the entire customer lifecycle. AI “blurs” the line between where advertising ends and product use begins.

Recommendations

Artificial intelligence brings not only new tools to marketing, but also new challenges. Understanding the atypical effects of its impact allows businesses to think outside the box and prepare for the next phase of digital evolution. In conclusion, here are some useful conclusions and recommendations:

  • Transparency instead of the illusion of anonymity. Consumers are no longer anonymous on the internet. Use AI to better understand your customers, but be ethical and open about data collection, for example, through cookies. This builds trust.
  • The brand as a source for AI. If your customers use AI for advice, make sure that AI “knows” your brand and provides relevant information. Invest in GEO and structured data to improve visibility in AI recommendations.
  • Algorithmic trust. Build a reputation not only among people, but also among algorithms. High ratings, reviews, and activity on platforms help your brand gain an advantage in recommendations. Be transparent about using AI to interact with customers.
  • Adapt to new behavior patterns. Monitor how your audience uses AI. If customers come in already prepared (knowing what they want), change your approach.
  • A unified experience on all fronts. AI brings together marketing, product, and service. Invest in platforms that provide a holistic view of customer interactions, allowing you to deliver relevant offers at every stage of the consumer journey.

Artificial intelligence is not “the end of the marketing profession,” as is sometimes dramatized. It is a powerful catalyst for change that, in skilled hands, opens up incredible opportunities for a deeper understanding of the consumer and building long-term relationships with them.

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