At Groceryshop this year, AI’s role in revolutionizing grocery was a key theme.
In particular, we learned how AI continues to not only transform the buyer journey, but how brands optimize for it. Brands are now fighting for space and attention on 4 shelves: physical, digital, social, and agentic. And from the keynote stage to networking after-parties, the rapid adoption (already over 50%!) of AI shopping was a regular topic of discussion, underlining the urgency that many brands feel in adapting to this new LLM-powered frontier.
But with every challenge also comes opportunity, and AI shopping is rich with potential for smart brands that are prepared to capitalize on this exciting development.
Key Stats: AI Shopping Adoption
| 60% | of consumers use AI for shopping at least sometimes |
| 77% | of retail media networks are investing in agentic ad formats |
| 96% | of shoppers who use AI plan to maintain or increase use over time |
| 50% | larger baskets for shoppers who use Instacart’s AI assistant |
Standing Out on the Agentic Shelf
AI-Generated Shortlist Replaces Traditional Shelf Space
With agentic shopping, customers are now presented with just 3-5 recommended items instead of thousands of options on physical or digital shelves. Shortening the path from inspiration to conversion, AI is making shopping faster and more deliberate, reshaping not just what and where shoppers buy, but also how they build their baskets.
LLM Training Data Creates Visibility Gaps
Euromonitor and Bain data show that several skincare brands and retailers have low LLM share of voice but strong market share. LLMs pull liberally from Reddit, Wikipedia, YouTube, and similar social content; if brand claims don’t align with community sentiment, AI visibility will decline.
Brand Requirements for AI Discovery
To be successful in AI-powered shopping, brands need to be:
- Findable for relevant missions
- Machine-legible through structured, standardized data
- Chosen for an AI-generated shortlist
- Fulfillable via a visible, in-stock path to purchase
Remember: product information should always use natural language, connecting facts to shopper outcomes and displaying accurate availability data.
Pacvue recommends:
- Use complete, consistent, and machine-readable product data across all your channels.
- Integrate with common agent protocols (e.g., ACP for ChatGPT & UCP for Google).
- Adhere to retailer-specific data compliance rules.
- Build repeatable processes to ensure accurate product, pricing & inventory data across platforms.
- Use Pacvue Prism to determine which agent channels drive conversions and profitable revenue
Check how AI-ready your brand is with our agentic commerce readiness scorecard.
Staying Ahead of the Grocery Curve
Outcomes Are the New Categories
Shoppers increasingly choose products that produce a desired outcome, not just the top option in a specific category. Competitive sets now extend across aisles, creating opportunities for brands like Purely Elizabeth to compete across cereal, oatmeal, snacks, and cookies simultaneously.
The Unbranded Search Advantage
If you’re only showing up after consumers explicitly search for your brand, you’re already too late. To remain competitive, brands need to appear for category-level and problem-based prompts higher in the funnel, reaching consumers as soon as inspiration strikes.
Price Transparency & Loyalty Intensifies Grocery Competition
As AI tools enable shoppers to compare the costs of entire baskets across retailers, grocers will increasingly rely on loyalty programs and discounting to reach and retain customers. Already, Instacart reported that grocers using same-as-in-store pricing grew 10% faster, as surging fuel costs make online shopping even more attractive.
The Retail Media Measurement Gap
Only 31% of retail media network leaders think their networks are competitive with their peers, down 14% YoY, while just 28% trust their market-sizing methodology and a full 7 out of 10 feel like they struggle to keep pace in terms of pricing and capabilities. The assumptions behind growth are being questioned now more than ever.
Pacvue recommends:
- Target consumers based on the outcomes they’re trying to achieve (e.g., “high-protein meal”), not the categories they browse.
- Dedicate 20-30% of your ad spend to upper-funnel campaigns, focusing on category searches, problem-based searches, and social platforms (discovery commerce).
- Stop measuring in silos and start testing how ad placements perform when paired with loyalty offers, discount pricing, or new creative/messaging.
- Measure incrementality daily, not quarterly, and shift budget or adjust ad strategy as soon as performance dips.
- Close the measurement-activation gap by moving from action to analysis in a single workflow with Pacvue Agent.
Winning Grocery in Q4 and Beyond
It’s clear that AI shopping adoption is only going one way—up.
And in this increasingly post-funnel world, where shoppers often discover, consider, and purchase in a single session, channels no longer neatly fit into funnel stages. To capture insights and execute on them at scale across multiple platforms, you need to optimize from a single interface, not dozens of disparate logins. You need a commerce-native platform that maps media channels to hard, business outcomes.
Learn more about Pacvue Prism and the Agentic Commerce Grid.
