Groceryshop 2026 runs September 22 to 24 at Mandalay Bay in Las Vegas. More than 4,000 retail professionals from over 50 countries will attend, with one in three at the C-suite level. The confirmed speaker list includes senior leaders from Instacart, Kroger, Sam’s Club, DoorDash, Mercado Libre, Dollar General, BJ’s Wholesale Club, and Diageo. The Day 1 keynote belongs to Chris Rogers, CEO of Instacart. Amazon sponsors the first private industry session: “Converting Signals into Sales: Closing the Loop with Agentic AI Across Retailers and Brands.”
Rocquan Lucas, VP of content at Groceryshop, summarized the 2026 moment in one sentence: “Shopping baskets in grocery, convenience, dollar and drug channels are being reshaped at once, by AI, GLP-1, and retail media.” That framing is accurate. It is also incomplete. Three forces reshaping the basket simultaneously is a strategy problem. Whether the retailer’s systems can detect and respond to that reshaping in real time is an operations problem. Groceryshop addresses the first. Most retailers attending have not yet solved the second.
The sessions at Groceryshop 2026 will be excellent. The harder question is not what happens in the room at Mandalay Bay. It is what happens when those 4,000 retail leaders return to their stores on September 25 and try to execute on what they heard.
What the Groceryshop 2026 Agenda Actually Tells You
Conference agendas are not predictions. They are documentation of where the industry’s leading organizations are already placing their bets. Amazon sponsoring a session on closing the agentic AI loop on Day 1 is not a statement about the future. It is a statement about what Amazon is already doing and believes retailers need to understand now. Similarly, the Instacart CEO keynoting Day 1 is not a coincidence. Instacart’s strategy is the most complete demonstration currently operating of what a connected retail commerce layer looks like in practice. It spans Caper Carts on the store floor, pharmacy delivery, and AI-powered shopping through ChatGPT.
Additionally, the dedicated AI-Powered Shopping Series this year explicitly covers GEO and AEO tactics: the mechanics of making products discoverable to AI agents rather than search engines. As I described in the Generative Engine Optimization analysis, the retailers who solve this problem in 2026 will have a compounding advantage in the AI discovery layer. Their competitors will spend 2027 trying to close it. Groceryshop 2026 is bringing that conversation to 4,000 decision-makers at once. That is not the same as those 4,000 decision-makers having the infrastructure to execute on it.
The Gap Between the Conference Room and the Store Floor
What Amazon Will Say and What It Requires
The Amazon session title is precise: “Converting Signals into Sales: Closing the Loop with Agentic AI.” Closing the loop means the AI agent does not just surface a recommendation. It completes the transaction, confirms the inventory, updates the pricing, and feeds the outcome back into the model that generated the recommendation. That loop requires four things simultaneously. Clean real-time product data. Inventory accuracy at the item level. A checkout infrastructure that AI agents can transact through. A data pipeline that captures what happened and returns it to the system.
Consequently, a retailer who leaves the Amazon session inspired to close the agentic AI loop faces a common constraint when they return to the store. The on-hand number is a nightly batch. Nobody has audited the ESL in a month. The checkout infrastructure has no API accessible to an external agent. In that store, the loop cannot close. As I described in the agentic commerce inventory accuracy analysis, the most common failure in agentic retail implementations is not the AI model. It is the operational data layer underneath it.
What the Instacart Keynote Signals for Every Other Retailer
Chris Rogers keynoting Day 1 at Groceryshop 2026 is significant beyond the content of his remarks. As I described in the Kroger Instacart pharmacy integration analysis, Instacart is systematically building the commerce layer between grocery retailers and their customers. That layer now spans in-store hardware, AI discovery, pharmacy delivery, and checkout infrastructure. The keynote confirms what the past 18 months of announcements have been building toward.
For the regional grocers and mid-size chains in that Groceryshop audience, the Instacart keynote raises a strategic question more urgent than anything in the session itself. How much of your customer relationship are you comfortable routing through a platform whose commercial interests and yours are aligned today but may diverge tomorrow? That question does not have a universal answer. However, it needs a deliberate answer from your organization, not one that emerges by default as each individual integration decision accumulates.
The Three Themes and What Each One Requires Operationally
AI-Powered Shopping: Discoverable Before You Are Transactable
The AI-Powered Shopping Series at Groceryshop features research from Bain, Kantar, and Euromonitor International alongside GEO and AEO tactics from CPG leaders. The sessions will document how leading brands ensure their products appear when AI agents search on behalf of shoppers. That is the discovery layer. Furthermore, as I described in the AI retail discovery and transaction analysis, discovery without transactability is an incomplete strategy. A brand whose product the AI agent recommends but cannot purchase in the same interface loses the conversion advantage that makes AI-referred traffic so valuable.
Retail Media: From Awareness to Closed-Loop Attribution
Retail media at Groceryshop 2026 centers on measurement and the next phase of growth. The industry has spent three years building retail media networks. The 2026 conversation is about proving that the ad spend actually drove the sale. Closed-loop attribution requires connecting the ad impression to the transaction. That requires the same clean data layer that agentic commerce requires. A retailer whose inventory data is unreliable, whose POS and e-commerce availability engines disagree, and whose transaction data takes 24 hours to process cannot close the attribution loop. It cannot close the agentic AI loop either. The infrastructure problem is the same. The urgency depends on which budget owner is feeling the pressure first.
GLP-1: The Demand Shift AI Systems Have to Detect
The GLP-1 theme at Groceryshop 2026 is the most operationally interesting of the three. GLP-1 medications are producing a measurable shift in what grocery shoppers buy: less volume overall, fewer impulse items, more protein and produce. For a retailer running AI-powered demand forecasting and assortment optimization, a GLP-1 shopper buying differently is not an anomaly. It is a signal. The question is whether the AI system is designed to detect that the signal is structural, not seasonal, and adjust its models accordingly. A forecasting system that treats the GLP-1 demand shift as noise will systematically over-order the wrong categories. It will under-order the right ones. Specifically, that error compounds every planning cycle until someone notices the inventory problem in a margin report.
What This Means for LatAm Retailers
Groceryshop draws attendees from over 50 countries, including a meaningful presence from Latin American retail. Mercado Libre is a confirmed speaker. The GLP-1 theme is less immediately relevant in LatAm markets where medication adoption is lower, but the AI-powered shopping and retail media themes apply directly. Moreover, the operational readiness gap that Groceryshop will surface for U.S. retailers is more pronounced in LatAm formats. Data infrastructure is earlier stage. Inventory management systems are less integrated. Retailers are still building real-time data pipelines between the store floor and the digital commerce layer.
LatAm retailers attending Groceryshop who leave with a clear understanding of that infrastructure gap will use the conference most productively. The ones who leave excited without auditing the infrastructure underneath them will face the same execution gap that has stalled AI implementations in more mature markets.
Three Questions Worth Answering Before September 22
Groceryshop 2026 will surface the most important conversations in grocery retail this year. The retailers who get the most from those conversations will be the ones who arrive with honest answers to three questions that the agenda will not ask directly.
Can Your System Close the Loop Amazon Is Describing?
The agentic AI loop from signal to sale requires real-time inventory accuracy, API-accessible checkout infrastructure, and a data pipeline that captures transaction outcomes and returns them to the model. If any of those three components is missing or unreliable, your organization cannot close the loop regardless of which AI platform you integrate with. Knowing which component is your constraint before the session starts means you leave with a specific action item rather than a general aspiration.
How Much of Your Customer Relationship Is Already Routed Through a Third Party?
After the Instacart keynote and the retail media sessions, most attendees will have encountered three to five platform integration opportunities. Each one is individually reasonable. Taken together, they describe a customer relationship that is increasingly intermediated. The retailers who arrive at Groceryshop with a clear answer to how much intermediation they are comfortable with will make better integration decisions. By contrast, those who evaluate each opportunity in isolation without a framework for the cumulative effect will not.
Does Your AI System Know the Difference Between a Structural Shift and an Anomaly?
The GLP-1 theme will generate the most discussion at Groceryshop among retailers already seeing the demand shift in their category data. The operational question underneath that discussion is whether the forecasting and assortment AI those retailers are running can distinguish a structural change in shopper behavior from seasonal variation. If the system cannot, it will correct toward historical baselines that no longer describe the shopper in the store. That is not a conference problem. It is a model design problem that the conference will make visible but not solve.
Groceryshop 2026 will be one of the most important retail technology events of the year. The retailers who leave with a clear-eyed assessment of their own operational readiness will be the ones who can act on what they heard. The gap between knowing what the agentic AI loop requires and having the infrastructure to close it is where most retail AI investments stall. Three weeks is enough time to start closing it.
If you are preparing for Groceryshop 2026 or evaluating your AI infrastructure readiness before the fall conference season, connect with me here or reach me on LinkedIn. I am happy to walk through the framework we use across the U.S. and Latin America.
Adriana Rivas is a retail technology executive and AI strategist, and the founder of a U.S.-based hardware company specializing in self-service kiosks, POS systems, electronic shelf labels, and digital signage deployed across the United States and Latin America. She is the award-winning author of How to Implement Self-Service Without Failing (Amazon #1 Hot New Release, Silver Nonfiction Book Award 2025) and recipient of the Gold Stevie® Award, Thought Leader of the Year 2026. She is also recognized by Thinkers360 as the #7 Global Thought Leader in Retail and a Certified Master Expert in Retail.