Ever find yourself hopping between Amazon and Google while shopping? You're not alone. We all do it. We search for a product, then open a new tab to research reviews or compare different models. This fragmented shopping experience is a pain point for consumers and a challenge for e-commerce platforms. New research explores how AI can bridge this gap by bringing information seeking directly into product search, potentially transforming how we shop online. Imagine having relevant questions and answers pop up right as you browse, saving you the hassle of endless tabs and searches. This is the promise of Q&A recommendation systems. By understanding the stages of a typical shopping journey—from initial exploration to comparing options and final consideration—these AI-powered systems can provide timely information tailored to each step. Early in your search, you might see general questions like, "What are the different types of coffee machines?" As you narrow down your choices, the questions become more specific: "How easy is this coffee maker to clean?" These systems leverage the power of large language models (LLMs) to generate both questions and answers. The models are fed vast amounts of data, including product specifications, customer reviews, and even external knowledge, allowing them to create relevant and helpful content. However, building such a system comes with challenges. Ensuring the accuracy of information, handling the vast scale of product catalogs, and personalizing the experience are just a few hurdles. One approach is to use a combination of human review, automated evaluation, and real-time user feedback to constantly refine the quality and relevance of the Q&A pairs. This research also delves into how to best optimize these systems using user engagement data. Clicks, purchases, and even how long you hover over a question can all provide valuable signals. This feedback loop allows the system to learn which questions are most helpful and tailor future recommendations accordingly. The future of online shopping might be a lot less fragmented and a lot more conversational. By integrating information seeking seamlessly into the product search experience, AI promises to empower consumers with the knowledge they need, right when they need it, ultimately making online shopping faster, easier, and more satisfying.