AI shopping is transforming how brands connect with consumers, pushing them to focus on both being discovered naturally and converting through paid promotions. For the past two years, the advice for brands has largely been the same: ensure that AI systems understand and recommend your brand when a customer asks a question. This approach, often called GEO (Getting Exposure Online) or AEO (AI-Enabled Optimization), aims to make sure that AI can retrieve accurate, relevant information and suggest a brand when needed. That strategy may be shifting, however, after Amazon revealed a significant finding in its Q2 results. According to CEO Andy Jassy, customers who click on paid "Sponsored Prompts" within Alexa for Shopping are 48% more likely to make a purchase and spend 21% more than those who don’t. While this data comes directly from Amazon rather than an independent source, it highlights a growing trend: paid advertising is becoming an integral part of the AI shopping experience, not just an add-on. This shift is important because AI shopping is evolving into two distinct models. One is open assistants, like Alexa or Google Assistant, which aim to recommend the best products they can find. The other is closed ecosystems, like Amazon, where the platform controls the commercial environment around recommendations. For brands, this means that visibility alone may not be enough — the value of being seen depends heavily on the platform’s structure and how advertising fits into the customer journey. The split between these models reflects a deeper tension in AI shopping. Until recently, visibility through AI was seen as a single goal: ensure that a brand is understood, cited, and recommended. But when a platform also has a business model based on advertising, the dynamics change. Amazon and Google are both moving toward integrating ads directly into the AI conversation, where recommendations and promotions can occur in the same interaction. This creates a commercial incentive to push more advertising into AI-driven shopping experiences. While GEO and AEO remain important for ensuring visibility, they may not be enough on their own. Brands can be highly visible in AI recommendations but still fail to convert that visibility into sales. Additionally, even strong paid visibility can't compensate for poor product information. AI still needs accurate data about what a product is, who it’s for, and how it compares to alternatives. This is where a new approach, called agentic commerce optimization (ACO), is gaining attention. ACO goes beyond visibility by focusing on how AI systems make or influence purchasing decisions. Factors like price, availability, and delivery options all play a role. ACO can be broken down into five key areas: Completeness, Context, Citations, Correctness, and Customer Acquisition. The first four ensure that AI can understand and recommend a product, while the fifth focuses on whether that recommendation actually results in a customer. For brands, the challenge now is to understand how recommendations work on each platform and how advertising fits into the customer journey. They must also monitor which products are being surfaced, where competitors are gaining ground, and whether visibility translates into real sales. As AI shopping evolves from answering questions to influencing decisions, visibility becomes the starting point, not the end goal. Brands that combine the fundamentals of GEO/AEO with ACO — optimizing the five Cs and measuring revenue impact — will be best positioned to thrive in this new landscape.