Retail Media Unboxed

As AI agents begin playing a bigger role in how consumers discover, compare, and ultimately choose products, retail marketers face a fundamental shift: the customer may no longer be the only audience they need to win.

In this episode of Retail Media Unboxed, Laura Sammartino, SVP of Horizon Futures – Future of Consumer and Culture, explores why trust could prove more important than technology in determining the future of agentic commerce. She joins us to discuss the “control paradox” shaping consumer adoption, why brands must become discoverable to algorithms without sacrificing emotional connection with people, and how AI could reshape everything from product discovery and brand loyalty to measurement and post-purchase marketing.

Laura also explains the emerging “automation hangover,” why conversion alone may no longer tell marketers enough, and how brands could take on very different roles as optimizers, curators, and guarantors depending on what consumers are buying.

Agentic commerce may be one of the industry’s favorite new buzzwords, but beneath the hype is a much more practical transformation already taking place across retail media and e-commerce.

In this episode of Retail Media Unboxed, Ross Caveille, Co-Founder at Acorn-i, joins us to explore what brands can genuinely accomplish with AI agents today, from automating reporting and identifying anomalies to forecasting demand and connecting signals across retail media, DTC and social commerce. Ross explains why the most valuable applications are often the least glamorous, why proprietary data will become an increasingly important competitive advantage and why brands should resist trying to agentify their entire organizations at once.

The conversation also explores what businesses need to have in place before deploying agents at scale, including clean data, reliable infrastructure, interoperability, governance and clearly defined autonomy thresholds. Most importantly, Ross argues that the goal should not be replacing commerce teams, but removing repetitive operational work so people can spend more time on strategy, customer understanding and the decisions where human judgment still matters.

AI agents are supposed to transform commerce, autonomously researching products, comparing prices and eventually making purchases on our behalf, but the reality of how people actually shop suggests a considerably more complicated future.
 
In this episode of Retail Media Unboxed, we sit down with Justin Sparks, GM of Retail and Commerce Media at Teads, to separate the practical applications of AI in commerce from the hype. Sparks argues that the immediate opportunity isn't autonomous shopping at all, but AI-assisted research, particularly for expensive or complicated purchases where consumers genuinely benefit from having information synthesized for them. 
 
We explore why the infrastructure for true agent-to-agent commerce still has a long way to go, how LLMs could reshape product discovery before shoppers ever reach a retailer, and why publishers, reviews, Reddit, YouTube and the open web could become even more important as sources of trusted information. We also discuss what this means for retail media networks whose lucrative sponsored-search businesses depend on shoppers actually searching retailer websites, and why the arrival of conversational commerce could force retailers to rethink both monetization and the customer experience. 
 
Most importantly, Sparks challenges the idea that AI will make brands less important by turning shopping into a purely rational exercise. If AI recommendations are ultimately informed by reputation, preference, loyalty, trusted editorial coverage and the information surrounding a brand across the web, brand building may become more consequential in an agentic world, not less. 

5 Key Takeaways

1. Agentic research is arriving much faster than agentic purchasing.
The most compelling current use case for AI isn't handing over the credit card and allowing an agent to shop autonomously, but helping consumers navigate complicated, high-consideration purchases such as televisions, electronics or travel. For habitual purchases and everyday CPG products, autonomous agents may actually introduce more complexity than they remove. 

2. The open web could become more important, not less.
LLMs need reliable information to formulate useful recommendations, which means publishers, editorial reviews, consumer reviews, YouTube, Reddit and other sources can influence what products ultimately enter an AI-generated consideration set. Brands therefore need to think about their visibility across the information ecosystem rather than focusing exclusively on what happens at the retailer. 

3. GEO could become a new battleground for challenger brands.
Smaller brands have an opportunity to establish themselves inside AI-driven product discovery by ensuring accurate and consistent information appears across publishers, reviews and user-generated content. If AI systems increasingly mediate the beginning of product research, earning visibility in the sources those systems rely upon could become as strategically important as conventional search visibility. 

4. AI may make brand building more important rather than less.
An AI can rationally compare price, availability and specifications, but consumers still bring preferences, loyalty and perceptions of quality into the process. If those preferences become part of the context agents use to make recommendations, strong brand equity becomes a signal that algorithms must account for rather than something algorithms eliminate. 

5. Retail media's sponsored-search model could face a fundamental challenge.
Retail media networks have built significant businesses around monetizing search-results pages, but AI-driven discovery could mean shoppers arrive at retailers already knowing considerably more about what they want. If that reduces searches and page views inside retailer environments, RMNs will need new ways to monetize conversational interfaces and capture demand without compromising the customer experience.

Retail media has exploded into one of marketing's fastest-growing sectors, but behind the scenes, many retailers are still trying to connect dozens of disconnected systems while advertisers struggle to navigate an increasingly fragmented ecosystem.

In this episode of Retail Media Unboxed, Drew Cashmore, Chief Strategy Officer at Vantage, explains why retail media has evolved far beyond an advertising channel into a competitive business platform. He discusses why composable architecture is becoming essential, why technology investment—not just media sales—will determine which retailers succeed, how interoperability and standardized APIs could unlock the industry's next phase of growth, and why the industry's obsession with measurement standardization may be distracting from the much bigger opportunity.

Retail media has become one of marketing's most measurable channels, but that doesn't necessarily mean it's measuring what matters.

In this episode of Retail Media Unboxed, Leah Logan, VP of Retail Media Transformation at Inmar Intelligence, explains why traditional attribution models fail to capture much of today's consumer journey, particularly as creators become a larger influence on discovery and purchase decisions. She discusses why brands need to think beyond last-click attribution, why creator content should be treated as an asset rather than simply another media buy, and how retail media networks can compete for larger brand budgets by focusing on consumer behavior instead of isolated tactics.

Leah also shares why planning, creative strategy, and business outcomes—not just targeting and measurement—will define the next generation of successful retail media networks.