The traditional search, comparison, and purchasing model is being replaced by an intelligent experience driven by AI agents. AI will reshape consumer decision-making, bringing structural challenges and new opportunities to e-commerce. (Background: a16z's bold prediction: Will vibe coding lead to a winner-takes-all scenario?) Have you ever wondered why Google could become a $2 trillion giant while Wikipedia remains a non-profit organization? The answer is simple: the magic of commercial searches. When you search for 'how many protons are in a cesium atom', Google doesn't make a dime. But when you search for 'the best tennis racket', it starts printing money. This asymmetry defines the essence of the entire search economy. Now, with the rise of AI, this balance is being fundamentally disrupted. Recently, I read an in-depth analysis by a16z partners Justine Moore and Alex Rampell, whose insights into how AI is reshaping the e-commerce landscape deeply shocked me. They not only analyzed the threats Google may face but, more importantly, painted a new picture of e-commerce in the AI era. In this picture, the traditional search-comparison-purchase model is being replaced by an intelligent purchasing experience driven by AI agents. I spent a lot of time thinking about their viewpoints and, combining them with my observations of the industry, I would like to share some deeper reflections. Google's true crisis: it's not about search volume, but value migration. Justine mentioned a point in the article that impressed me: even if Google loses 95% of its search volume, its revenue could still grow as long as it retains those queries with commercial value. This perspective sounds counterintuitive but actually reveals the core secret of the search economy. After deep contemplation, I found that there is a more profound issue behind this: AI is changing the location of value creation. In the traditional model, Google plays the role of an information intermediary. Users have purchasing intent, Google provides search results and ads, merchants gain traffic, and Google collects advertising fees. This is a relatively simple three-party game. But the emergence of AI agents has disrupted this balance. When ChatGPT or Perplexity can directly answer the question 'what is the best tennis racket' and provide specific recommendations, why would users still need to click on Google’s ad links? More importantly, AI is not just answering questions; it is redefining 'search' itself. Our previous search behavior was: ask a question → get a list of links → click to view → compare information → make a decision. The process of AI agents is: describe needs → obtain recommendations → directly purchase. The intermediate comparison and research stages have been greatly compressed or even disappeared. This means traditional search engines not only lose query volume but also lose their crucial position in the decision-making chain. From the testimony of Apple’s Senior Vice President Eddy Cue in the DOJ antitrust trial in May 2025, we can see clues. He stated that Safari's search volume has declined for the first time in over twenty years, and this news directly caused Alphabet’s stock price to drop nearly 8% in a single day, evaporating over $150 billion in market value. Although Google's Q2 financial report shows that search revenue is still growing, indicating that the main loss currently is low-value queries, the direction of this trend is clear. I believe that Google faces not just simple competitive threats but structural challenges to its business model. When AI can directly complete the entire process from intent recognition to purchasing decision, the traditional 'traffic → advertising → conversion' model becomes inefficient or even outdated. What Google needs is not a better search algorithm but a whole new business model to adapt to AI-driven consumer behavior. Five types of purchasing behavior transformed by AI: from impulse to deep thought. Justine categorized purchasing behavior into five categories, ranging from impulse purchases to significant life purchases, each of which will undergo varying degrees of change in the AI era. I find this classification framework very accurate, but I want to analyze the psychological mechanisms behind each type of purchasing behavior at a deeper level, and how AI reshapes these mechanisms. Impulse purchases seem to be the area least affected by AI, as impulsiveness implies a lack of rational research process. However, I think this judgment may be overly superficial. The true power of AI lies in predicting and guiding impulses. Imagine, when you see a funny T-shirt on TikTok, AI has already analyzed your browsing history, purchase records, social media activity, and even your emotional state, then pushes the product that best fits your current psychological needs at the most precise moment. This is not just simple algorithmic recommendations but a deep understanding and manipulation of human impulsive psychology. I believe this personalized impulse guidance could make impulse purchases more frequent and precise. The AI transformation of routine essentials is the easiest to understand and implement. However, I noticed an interesting phenomenon: as AI begins to take over our daily purchasing decisions, our consumption habits may subtly change. For example, AI may adjust your purchasing timing and quantity based on price fluctuations, inventory conditions, or even weather forecasts. A smart AI agent might discover that a certain brand is on sale a week before your laundry detergent runs out, thus suggesting you buy it in advance and try it. This kind of 'smart arbitrage' behavior may lead consumers to unknowingly get better value for money while also forcing brands to rethink their pricing and promotional strategies. Lifestyle purchases are the area where I believe AI will have the greatest impact. These types of purchases are characterized by a certain price threshold, personal taste, and a need for a certain level of research. Justine mentioned products like Plush, but I think that's just the tip of the iceberg. The real revolution will come from AI's deep learning of personal styles and preferences. Imagine an AI assistant that not only knows what you have purchased in the past but also understands your body shape, skin tone, lifestyle, social circles, and even your aspirations. It can recommend not just individual products but entire outfits, even pathways for upgrading your lifestyle. This level of personalization is unattainable for traditional e-commerce platforms. The AI transformation of functional purchases is the most complex and challenging. These types of purchases usually involve large expenditures and long-term use, and consumers need not just product recommendations but also expert advice. I believe a new category of AI applications will emerge here: AI consultants. These AIs will not only have rich product knowledge but can engage in deep conversations similar to human sales experts. They can inquire about your specific needs, usage scenarios, budget constraints, and even your future plans, then provide highly personalized suggestions. More importantly, these AI consultants are cross-brand and will not be biased due to commissions or inventory.

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