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Walmart's experiment with ChatGPT-based shopping resulted in smaller carts and lower conversion rates. This is because agents fulfill precise, immediate needs (e.g., 'buy paper towels') rather than encouraging the broader, more lucrative browsing behavior that occurs on a retailer's own website or app.
The true value of AI in commerce isn't in automating the final click to buy, as checkout is largely a solved problem. The significant user need is leveraging AI for deep research on high-consideration purchases. Facilitating the transaction is less valuable than providing trustworthy, comprehensive information.
Large brands like Target are using ChatGPT apps as high-intent lead generators rather than for full-funnel transactions. The app helps users build a shopping cart within the chat interface and then hands them off to the main website to complete the purchase. This reduces integration complexity while capturing high-value users.
The idea of independent AI agents autonomously shopping online is failing as platforms block them to protect ad revenue. The sustainable model, already adopted by ChatGPT, involves agents surfacing sponsored product listings for affiliate revenue, not bypassing the platform's core advertising business model.
Consumer search behavior is shifting from browsers to AI assistants. E-commerce brands must adapt by treating agents like ChatGPT as new traffic sources. This requires making product data discoverable via APIs to enable seamless research and purchasing directly within conversational AI platforms.
For OpenAI's commerce features to succeed, it's not enough to build one-click checkout. They must fundamentally retrain hundreds of millions of users to trust a new purchasing workflow inside a chatbot, breaking deeply ingrained habits of searching on ChatGPT then buying on Google or Amazon.
AI shopping agents will disrupt e-commerce models that rely on human browsing for data collection, recommendations, and upsells. When agents perform these tasks programmatically, sellers lose this crucial interaction and must pivot to building agent-friendly interfaces and incentives, effectively selling to an algorithm.
AI agents shop based on optimized specs, not human heuristics like brand trust. This shift to "agentic commerce" could neutralize the power of major brands like Walmart and Amazon, and eliminate the interpersonal relationships that sustain local, small businesses.
OpenAI's 'instant checkout' failed to gain traction as users preferred browsing over buying directly in-chat. The feature also demanded intensive, hands-on support for a very small number of merchants, making it unscalable and leading to the strategic shift to an app-based model.
Just as newspapers ceded their audience to Google for traffic, retailers are being tempted to let AI chatbots handle customer interactions. This trade sacrifices brand identity and direct customer relationships for short-term volume—a historically catastrophic move that leads to commoditization by an aggregator.
The early dream of AI agents autonomously browsing e-commerce sites is being abandoned. The reality is that websites are built for human interaction, with bot detection, fraud prevention, and pop-ups that stymie AI agents. This technical friction is causing a major strategic pivot in AI commerce.