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Key Takeaways:
- AI is shifting product discovery from products to problems. Shoppers are increasingly using natural-language prompts to find solutions based on occasions, budgets, preferences, and needs rather than searching for individual products.
- Consumers remain in control, but AI is influencing purchase decisions. AI shopping assistants are becoming more involved in product recommendations, consideration, and purchasing tasks, creating new opportunities and challenges for brands.
- Structured product information is essential for AI-driven commerce. Brands need accurate, contextual product attributes, pricing, and availability data to remain relevant to both shoppers and AI-powered shopping experiences.
- Traditional engagement metrics don't tell the full story. Clicks alone cannot explain shopper intent or purchase outcomes. Brands need greater visibility into what happens between media engagement and retail sales.
- Connected commerce intelligence is becoming a competitive advantage. Integrating shoppable media, retail intelligence, and commerce data helps brands understand shopper behavior, improve product visibility, and connect discovery to measurable retail outcomes.
How AI and changing shopper behavior are reshaping product discovery
At Groceryshop 2026, one thing stood out: product discovery is changing, and brands need to address product visibility. AI is helping shoppers move from a need or occasion to a relevant basket with less effort, while consumers are becoming more intentional about what they buy and more comfortable getting help making those decisions.
For brands, that changes what it means to be discovered, considered, and ultimately chosen.
Shopping is moving from products to problems
One of the clearest examples came from DoorDash co-founder Andy Fang: “People aren't looking for SKUs. They're trying to solve problems.”
Instead of searching for individual products, a shopper might describe an occasion, a meal, a budget, or a dietary need and let AI help assemble the right basket. DoorDash is already seeing shoppers use natural-language prompts in this way, while Instacart described a similar future where a request such as a healthy family meal under $40 can be translated into products based on preferences, budget, store choice, and availability.
For brands, that means discovery is becoming less about matching a specific search term and more about being relevant to the need behind it.
The shopper is still in control, but they’re not deciding alone
That raises a bigger question: who owns the purchase decision when AI becomes part of the journey?
Fang’s view was clear. The consumer still owns the intent to buy. AI can understand preferences and make the journey easier, but DoorDash is deliberately not designing an experience that removes the shopper’s sense of control.
At the same time, consumers are becoming more comfortable giving AI greater influence. According to Accenture's Consumer Pulse Research 2026, 32% of consumers are willing to let an AI agent make purchase decisions within defined boundaries, while 74% would allow an agent to execute specific commerce tasks on their behalf.
Awareness and loyalty still matter, but they may no longer be enough to secure the choice as AI creates new routes to purchase.
Awareness and loyalty still matter, but they may no longer be enough to secure the choice as AI creates new routes to purchase.
Brands need to be relevant to people and their copilots
If AI becomes another influence on what gets considered, product information needs to carry enough context for both the shopper and the systems helping them.
Grant used a simple example: “Great for families” might make sense to a person, but an AI system needs the attributes behind that claim, such as pack size, occasion, and storage. And even the right recommendation only matters if the product is actually available when the shopper is ready to buy, making retail intelligence increasingly important for monitoring product availability and retail performance.
For brands, that puts three things into sharper focus:
- Be understandable - Give shoppers and AI systems enough product context to understand where you fit.
- Be available - Make sure discovery can connect to what can actually be bought.
- Look beyond the click - Understand the behavior around media engagement, not just the engagement itself.
Seeing brand media through a new lens
That need to look beyond the click also shaped our own conversations at Groceryshop.
At The Wayfarer Club, our private Groceryshop event hosted at the Ray-Ban store, we brought together leaders from two dozen brands to discuss a shopper journey becoming more fragmented and harder to measure.
One theme that emerged from our conversations was the growing importance of connecting shoppable media engagement to retail outcomes. As brands gain access to more shopper data, the opportunity lies in understanding how those interactions translate into retailer traffic, purchase intent, and measurable retail performance.
That matters even more as AI-driven discovery creates new routes into the journey. A click can tell you that someone engaged, but connecting that engagement with product availability, retailer activity, and downstream shopping behavior provides a more complete picture of the shopper journey.
The path to purchase is changing
The shopper may still own the decision, but brands now have more influences to account for along the way.
For enterprise brands, these changes highlight the growing importance of commerce enablement: connecting product discovery, shopper intent, retail availability, and purchase outcomes across an increasingly fragmented journey. As AI-powered shopping experiences evolve, brands need both the commerce data that makes their products discoverable and the retail intelligence that helps turn shopper engagement into measurable results.
Wayvia helps brands connect these moments through shoppable media, retail intelligence, and commerce data, providing greater visibility into the behaviors that connect shopper engagement to retail sales.
Frequently Asked Questions
What were the biggest takeaways from Groceryshop 2026?
Groceryshop 2026 highlighted how artificial intelligence, changing consumer expectations, and fragmented shopping journeys are reshaping retail commerce. Key themes included AI-powered product discovery, shopping assistants, product availability, and the growing importance of understanding shopper intent. For brands, success increasingly depends on connecting product visibility, commerce data, and retail performance to measurable purchase outcomes.
How is AI changing the shopper journey?
AI is transforming the shopper journey by helping consumers discover products based on their needs, preferences, budgets, and occasions rather than individual search terms. Platforms such as DoorDash and Instacart are exploring natural-language shopping experiences that translate consumer requests into relevant product recommendations. This creates new opportunities for brands to influence purchase decisions through accurate, contextual product information.
What is agentic commerce, and why does it matter for brands?
Agentic commerce refers to AI-powered systems that can assist with or execute shopping tasks on behalf of consumers, including product research, comparison, and purchasing. As consumers increasingly delegate shopping activities to AI assistants, brands must ensure their products are discoverable, accurately represented, and available across retail channels. Strong product data and commerce intelligence can help brands remain competitive as AI influences purchase decisions.
Why is product data important for AI-powered shopping?
AI-powered shopping systems rely on detailed product information to identify relevant recommendations. Attributes such as product size, intended use, dietary characteristics, pricing, and retailer availability help AI systems match products to specific consumer needs. Accurate, structured, and current commerce data improves a brand's ability to participate in AI-driven product discovery and support informed purchase decisions.
How can brands measure shopper intent beyond clicks?
Brands can better understand shopper intent by analyzing behaviors that occur between media engagement and retail purchase. Metrics such as retailer referrals, product availability, and downstream shopping interactions provide additional context beyond impressions and click-through rates. Wayvia helps enterprise brands connect shoppable media, retail intelligence, and commerce data to understand Purchase Intent and optimize the shopper journey.
