Instacart introduced an embedded checkout experience within ChatGPT through the emerging Agentic Commerce Protocol.
With this introduction, the company became the first partner to launch an app on ChatGPT that provides a complete shopping cycle from query to payment without the user having to leave the conversational interface.
Operationalization of agent commerce
This integration fixes broken links, or “handoffs,” in conversational commerce. Previously, AI models could suggest products or generate meal plans, but the execution phase required a deep link to another application or website, often leading to cart abandonment.
With this new development, users can interact with AI to plan their meals and have the system build their cart based on inventory at local retailers. The differentiator here is the checkout process. By leveraging the Agentic Commerce Protocol, transactions are processed directly within the chat interface using credit card flows powered by Stripe.
According to Nick Turley, vice president and director of ChatGPT, the goal is to connect AI suggestions directly to real-world services.
“Using ChatGPT directly into the Instacart app, users can go from meal planning to checkout in one seamless conversation,” said Turley. “This is another step in realizing our vision, where AI provides helpful suggestions, connects directly to real-world services, and saves people time and effort in their daily lives.”
This integration goes deeper than using standard APIs. Instacart served as an early contributor to the OpenAI Operator research preview, providing feedback to ensure the technology overcomes real-world constraints while adhering to established norms.
This “preview” involvement suggests that Instacart’s complex data environment, which includes tens of thousands of SKUs and dynamic inventory levels, served as a testing ground for OpenAI’s agent capabilities. Rather than simply adopting a tool, Instacart helped define the parameters of how its AI agents interacted with external fulfillment logistics.
Instacart’s introduction highlights why structured, real-time data is important when integrating with large-scale language models (LLMs). The effectiveness of an AI agent is determined by the data it has access to. Illusion in commercial situations, such as selling out-of-stock items, carries financial and reputational risks.
Anirban Kundu, CTO at Instacart, says that powering shopping within AI agents requires technology that can interpret highly local and ever-changing inventory. Instacart seeks to reduce the risk of “illusions” by basing its AI responses on a large dataset covering more than 1.8 billion product instances across 100,000 stores.
“Instacart and ChatGPT are redefining what is possible with AI-powered shopping,” said Kundu. “This experience, built on the Agentic Commerce Protocol, provides intelligent, real-time support in one of the most important parts of daily life: getting groceries for your family.
“Together, we are creating a seamless and secure way for people to turn simple conversations into real-world actions, helping customers move from inspiration to full carts delivered easily from the store to their door.”
Dual hire: customer care and internal efficiency
While the embedded checkout grabs the headlines, Instacart’s broader plans include a large-scale internal rollout. The company uses ChatGPT Enterprise to streamline internal workflows with the goal of accelerating the development of customer experiences. Additionally, we introduced OpenAI’s Codex to power our internal coding agent.
Two approaches provide operating models: Selling with AI (Agentic Commerce) and Building AI (Codex). This moves beyond individual pilots to an overall stance where generative models drive both revenue and R&D efficiency.
This development signals a shift in how brands view digital storefronts. Instacart’s approach seems to accept that consumer entry points are fragmented. Rather than forcing all traffic through its own apps, the company is positioning its infrastructure as a backend fulfillment layer for third-party AI platforms.
The company has clearly stated its intention to serve as a key partner for major AI players such as OpenAI, Google, and Microsoft, bridging the gap between AI inspiration and real-world realization. By incorporating its services into these broader platforms, Instacart aims to capture the growing demand that comes from outside of its native ecosystem.
Instacart implementation and availability on ChatGPT
This experience is currently enabled for users on desktop and mobile web platforms, but native mobile availability for iOS and Android applications will be rolled out soon.
To access this feature, users must link their accounts by calling a specific Instacart application within the ChatGPT interface (for example, by displaying the prompt, “Instacart, can you help me shop for apple pie ingredients?”). This opt-in mechanism ensures that data sharing is consensual and is an essential governance step for companies deploying consumer-facing AI agents.
This integration serves as a case study for agent AI for commerce. For retail and technology executives, the Instacart model shows that the next stage of digital adoption involves preparing API structures and data pipelines to serve “non-human” customers (AI agents) as reliably as human customers.
Data accuracy and real-time availability must remain a focus. Without these foundations, agent workflows cannot deliver a return on investment.
See also: OpenAI: Enterprise users can exchange AI pilots for tighter integration
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