As artificial intelligence moves from a novelty to a utility, its integration into our daily routines is reshaping industries. Nowhere is this more apparent than in e-commerce, where AI is evolving from a simple recommendation tool into a fully autonomous shopping assistant. We’re joined today by Zainab Hussain, an e-commerce strategist who has been at the forefront of this evolution, to discuss a groundbreaking new development where AI doesn’t just suggest products—it completes the entire shopping trip for you.
We will explore the intricate process of how a simple conversational prompt is transformed into a curated grocery cart filled with a shopper’s favorite brands from local stores. Zainab will also shed light on the new metrics for success in this era of “agentic commerce,” the technical collaboration required to embed secure payments directly into a chat, and the broader strategic vision behind making grocery shopping a native function of AI assistants. Finally, we will unpack what this shift means for consumer brands, who must now adapt from optimizing for search engines to optimizing for artificial intelligence itself.
The article notes a user can start a shopping trip by simply asking for “apple pie ingredients.” Could you walk us through the step-by-step process of how the app translates that prompt into a final cart, using real-time local inventory and a shopper’s past brand preferences?
It’s a fascinating process that feels like magic but is grounded in some incredibly sophisticated technology. When a user makes a request like that, the first thing that happens is they connect their Instacart account within the chat. This is the crucial link. From there, the AI models do two things simultaneously. First, they access the user’s personal shopping history—their past orders, their favorite brands, the things they buy repeatedly. Second, and this is what makes it so powerful, the system queries Instacart’s real-time data from its network of nearly 100,000 stores. It’s not just guessing what’s available; it’s seeing a live snapshot of local inventory and pricing. The AI then synthesizes all of this information to build a cart that is not only accurate to what’s on the shelves at that moment but also deeply personalized to the shopper’s tastes, before presenting it for a final review.
The piece refers to this new capability as “agentic commerce.” Beyond convenience, what key metrics are you tracking to measure the success of an AI completing an entire purchase on a user’s behalf, rather than just surfacing product suggestions? Please share any early results.
What’s critical to understand about agentic commerce is that we’re moving beyond clicks and impressions. The real measure of success is adoption and trust, which we can see in broader market trends. The early results are staggering and paint a very clear picture. We’re seeing an explosion of user interest in transacting this way. For instance, recent data shows that e-commerce traffic coming from AI-driven sources skyrocketed by 758% year over year. More specifically, within ChatGPT itself, the share of shopping-related queries jumped from 7.8% to 9.8% in just six months. When you factor in the platform’s overall 70% user growth during that time, it means shopping queries effectively doubled. This demonstrates a massive and rapidly growing consumer appetite to not just research but to act through these AI agents, which is the ultimate validation of this model.
Integrating payments seems crucial here. The text mentions “Instant Checkout” was co-developed with OpenAI and Stripe. What were the main technical challenges in building a secure, one-click payment flow directly into a chat interface, and what was that collaboration like?
The primary challenge is creating a transaction experience that is both completely seamless and absolutely secure, all without forcing the user to leave the conversational interface. You can’t just embed a clunky, traditional checkout form into a chat; it would destroy the entire experience. The solution was to build something entirely new, which led to the Agentic Commerce Protocol, an open-source framework developed in close collaboration with Stripe. This collaboration was essential because it combined OpenAI’s mastery of the AI interface with Stripe’s deep expertise in secure payment processing. The result is “Instant Checkout,” a system that handles the complex security and payment logistics behind the scenes, allowing the user to finalize a purchase with a single tap. It’s a testament to how deep partnerships are necessary to solve these next-generation commerce challenges, and we’ll see it become even smoother as digital wallets like Apple Pay and Google Pay are integrated.
This app builds on other AI tools like your “Cart Assistant.” How does this direct-to-consumer ChatGPT integration fit into your broader strategy to become the “grocery engine” for all major AI platforms, and what was the most surprising thing you learned during the development?
This ChatGPT integration is a cornerstone of a much larger vision. It’s not an isolated project; it’s the next logical step in a strategy that began with tools like our “Cart Assistant,” which major retailers like Kroger are already planning to implement. The ultimate goal for Instacart is to become the indispensable “grocery engine” that powers commerce across every major AI platform, whether it’s OpenAI, Google, or Microsoft. We are positioning our vast retail network and logistics infrastructure as the transactional layer for this new conversational web. By doing so, we connect the massive consumer reach of these AI agents directly to our retail partners, driving significant new demand. Perhaps the most surprising element in all of this has been the sheer velocity of consumer adoption. Seeing a 758% surge in AI-driven traffic in a single year confirmed our belief that we weren’t just building for a future possibility; we were racing to meet a present and accelerating demand.
Given the data showing e-commerce traffic from AI sources has soared, brands now face “AI optimization.” What does this partnership mean for a CPG brand’s visibility, and how must they adapt their strategy to be recommended by an AI agent instead of just ranking high in search?
This shift represents a fundamental change in how brands need to think about discovery. For years, the goal was Search Engine Optimization (SEO). Now, the frontier is “AI Optimization,” or AIO. It’s no longer enough to rank for keywords. When an AI agent is building a cart, it’s making choices on a user’s behalf based on trust and preference. For a CPG brand, this means visibility is now earned through personalization and historical data. The AI will prioritize the brand of flour a user has bought five times before, not necessarily the one with the best search ranking. Therefore, the new strategy for brands must focus on becoming a customer’s preferred, go-to choice and ensuring their product information is structured in a way that AI models can easily understand and trust. It’s a move from winning a search query to winning a spot in a shopper’s life, as interpreted by their AI assistant.
What is your forecast for agentic commerce over the next five years?
Based on the trajectory we’re seeing, agentic commerce will transition from a cutting-edge feature to a standard consumer expectation within the next five years. The friction between wanting something and having it will all but disappear. We have projections showing that traffic from large language models to retail sites will increase by over 500% for the 2025 holiday season alone, and that’s just the beginning. I foresee this capability expanding far beyond groceries into more complex and considered purchases, from planning a vacation to furnishing a room. The line between a conversation with an AI and a completed transaction will completely blur. Essentially, every AI assistant will become a fully-functional, hyper-personalized, and trusted storefront in our pockets.
