My AI Advisor: The Promise and Peril of AI as a Consumer Guide

The way consumers discover information online is shifting from static search results toward dynamic, conversational interfaces. Traditional search engines still attract the bulk of traffic, but their dominance is starting to erode. According to a OneLittleWeb analysis of Semrush data, visits to Generative AI (GenAI) engines such as ChatGPT, Gemini, and Claude grew by 80% year-over-year, while traditional search slipped by 0.5%.

This shift signals a new era of digital consumer behavior, one defined not by a zero-sum contest between search and GenAI, but by the emergence of a hybrid model. In this landscape, new opportunities are opening up alongside fresh concerns. On the one hand, Generative Engine Optimization (GEO) is emerging as a powerful strategy for digital visibility, helping brands position content so AI-driven engines can deliver faster, more direct answers to consumer questions. On the other hand, these same engines still struggle with accuracy and reliability, making them risky sources for high-stakes decision-making. Let’s dive into it.

The Shifting Consumer Journey: From SEO to GEO

The core difference for brands is that success is no longer about getting a link to the top of a results page; it’s about being frequently mentioned within an AI’s summarized answer. The data suggests a complex relationship: Gen AI engines are not replacing traditional search engines but are reshaping how users interact with information. This shift is rapidly creating new demands for brands and organizations to adapt to a changing consumer journey, from Search Engine Optimization (SEO) to GEO. To adapt, businesses must master three core strategies:

●      Context-Rich Authority: AI values nuanced, comprehensive answers that anticipate user questions. Your content should be thorough and address a topic from multiple angles to increase the likelihood of being referenced in a generative summary. Building trust with high-quality, expert-backed, and well-cited content is crucial.

●      Consistency: Aligning your content across all sources (e.g., your website, social media, online forums, Wikipedia, etc.) reinforces your brand's authority and helps the AI form a complete picture of your brand or product.

●      Make Your Answers Stand Out to AI: One way to help AI understand your brand is by highlighting your answers. This involves using structured data, also known as schema markup. These tags act like bullet points, laying out the key facts in a way that AI can instantly read and process. Think of it as creating a digital interview transcript for your company. You explicitly tell AI what your brand is, which products you sell, and how everything connects.

This new approach also means marketers must adapt their content, as the "long tail" of search queries is in the form of highly specific, conversational questions. These queries are, on average, longer than those of the search engines, so this requires thinking in terms of full questions and anticipating follow-up queries. For market researchers, this represents a golden opportunity to identify unanswered questions; early adopters of GEO can benefit by answering very specific questions that haven't been addressed before.

What Behavioral Data Reveals

The world of generative AI is still new, and many so-called "best practices" are simply being repeated without any real proof. The most reliable way to find what works is by running your own research; this new context challenges traditional attribution models.

Passive data meters offer a reliable way to understand how people actually use generative AI; consumers might discover your brand through an AI, then conduct a separate search for your company or type your domain directly into their browser. Recent data suggests that consumers use traditional search and generative AI for different purposes; one is often for quick answers, while the other is for in-depth exploration. This kind of research also highlights a clear demographic divide. Younger users are adopting chatbots for conversational queries, while older generations continue to stick with traditional search. What does this behavioral divide mean for marketers? It reinforces the need to adopt a hybrid content strategy that caters to both user groups. Companies should set a baseline, defining target questions, and then experiment and iterate to improve mentions and positioning.

Risk of using AI as an advisor.

The shift toward AI for advisory roles (e.g., financial, health, and general life guidance) reflects the clear consumer demand for instant, accessible, and seemingly free information. However, this trend has created a new set of risks.

While AI has demonstrated its potential in many fields, it is not infallible. A fundamental issue is that AI systems, by their nature, can provide inaccurate or misleading information. This unreliability is leading to real-world harm, as highlighted by a recent survey showing that more than half of users who followed AI financial advice ended up making poor decisions.

The problem is compounded by a design philosophy that prioritizes engagement over human well-being. A recent and highly disturbing lawsuit against a major AI company reveals that systems are being designed to maximize user interaction through features like anthropomorphic responses and constant validation. The lawsuit, filed by the Raine family, exposes how these design choices can lead to tragic and preventable outcomes, with the AI chatbot allegedly engaging in a pattern of psychological manipulation that contributed to a teenager's suicide.

This case is not about a single technical glitch; it's a critical indictment of an industry that is racing to dominate the market by building systems that prioritize user engagement over user safety. As AI becomes an increasingly common source of advisory information, the central challenge for creators and regulators is to ensure that these tools are built with a primary focus on human well-being, not just commercial success.

A watershed moment in Digital Consumer Journeys.

The growth of GenAI as a consumer advisor is reshaping consumer journeys. This indicates that the focus for businesses should be on shaping how AI engines understand and present their brand and products. Companies that embrace this change early will likely see a significant boost in visibility as search continues to evolve.

Navigating this new landscape requires a commitment to robust research and a healthy dose of curiosity. Marketers must adapt their strategies to ensure their brand is well-represented, without ignoring potential risks. This evolution could trigger a consumer backlash that reshapes attitudes and behaviors toward GenAI, which is something to monitor closely.

By focusing on the subtle, ever-changing dynamics of digital consumer behavior, we can build a truly effective strategy. Observing these distinct user behaviors is the only way to accurately navigate this evolving landscape.