Evan Lee Salim
Agentic AI is no longer a futuristic concept reserved for science fiction or speculative white papers. It has arrived, fundamentally altering the fabric of modern commerce media. As the digital marketplace shifts from a landscape of static search results to one of fluid, AI-mediated recommendations, brands and retailers are finding themselves in a race to define the next generation of consumer engagement.
The transition is rapid, structural, and definitive. To gauge the extent of this shift, a comprehensive study—"The State of Agentic Commerce (Media): How Agentic AI is Reshaping Control, Value and Monetization"—surveyed 750 consumers and 150 senior commerce media executives across the United States, the United Kingdom, and Germany. The findings suggest that we are entering a "decision economy," where the traditional metrics of ad placement are being replaced by the imperative of AI influence.
The Evolution of the Shopping Journey: A Chronological Shift
To understand where commerce media is headed, one must recognize how far it has come in a remarkably short window.
- The Era of Impressions (2010–2020): For the last decade, success in commerce media was defined by "share of voice" and visibility. The primary goal was to secure premium ad placements on high-traffic retail pages. If a consumer could see your product, you had a chance at conversion.
- The Era of Intent (2020–2023): As data-driven advertising matured, the focus shifted to intent. Retailers used behavioral data to serve ads that aligned with what a user was currently searching for or browsing, moving from broad visibility to targeted relevance.
- The Era of Agentic Influence (2024–Present): Today, we have moved beyond static searches. AI agents now act as intermediaries, filtering the noise of the internet to provide personalized recommendations. The bottleneck is no longer the "top of the funnel" in the traditional sense; it is the "shortlist" curated by an AI.
This transition has been accelerated by consumer demand. According to the research, 75% of U.S. consumers now express comfort with AI assisting in their purchasing decisions. Crucially, the data shows that as shoppers interact more frequently with AI, their comfort levels rise, suggesting that the barrier to adoption is not skepticism, but familiarity.
Supporting Data: The Consumer-Executive Divide
The survey data highlights a nuanced reality that challenges the assumption that consumers want full automation. While there is a broad appetite for AI, there is a clear "trust threshold."
The Trust Gap
Consumers are eager to offload the cognitive labor of shopping to AI. They appreciate the technology’s ability to compare specs, hunt for deals, and identify brands they might otherwise overlook (64% of consumers favor this). However, the "buy" button remains a human sanctuary.
- 20% of consumers are comfortable with AI acting completely independently to execute a transaction.
- 55% of consumers explicitly state that a purchase made by AI without their prior approval would be a "trust-breaker."
This distinction between shopping (the research and comparison phase) and purchasing (the final commitment of capital) is vital. For brands, the opportunity lies in the research phase, where the influence exerted by an AI agent can determine whether a product makes it onto the final, human-vetted shortlist.
The Executive Mandate
Industry leaders are mirroring this cautious approach. The research reveals that a mere 3% of commerce media executives favor a "fully autonomous" model where AI operates with total independence. The vast majority are prioritizing "human-in-the-loop" systems, where AI surfaces insights and proposes actions, but human oversight remains the final arbiter.
The New Rules of Commerce Media
As the industry pivots, Koddi—a leader in powering commerce media infrastructure—has identified four fundamental rules that will define the winners and losers in this new environment.
1. Research as the New Battleground
Since consumers are willing to let AI curate their options but want to retain the final say, the battle for the sale is being won during the research phase. Brands that successfully integrate their data into the ecosystems that power these AI agents will be the ones that appear on the shortlist.
2. Influence Over Placement
In the age of AI, "placement" is becoming an archaic term. If an AI agent recommends three products to a user, the products that are left out of that recommendation are effectively invisible. Therefore, the goal is no longer just buying a sponsored slot at the top of a page; it is optimizing for inclusion within the AI’s recommendation logic. 84% of surveyed commerce media leaders are already planning to shift budgets from traditional performance and search toward securing this visibility within AI-driven results.
3. Collaboration, Not Automation
The goal is not to eliminate human input but to scale it. The most successful organizations are those building infrastructure that allows for seamless human-AI collaboration. This involves real-time diagnostics, cross-network data synchronization, and tools that allow marketing teams to manage agentic outcomes with the same rigor they applied to traditional search engine marketing (SEM).
4. The Measurement Imperative
Investment in agentic AI is currently being hindered by a "measurement gap." One-third of advertisers report that current attribution models are insufficient for an AI-mediated world. With companies planning to allocate between $250,000 and $1 million to agentic AI products in the next year, the pressure to prove ROI is mounting. The industry is currently moving toward "agent-specific measurement," with 92% of leaders planning to invest in tools that can track the impact of AI-mediated journeys.
Implications for the Future of Commerce
The shift toward a decision economy carries profound implications for how retail media networks (RMNs) must structure their operations.
Fragmentation and the Need for Orchestration
One of the primary challenges identified by industry leaders is the fragmentation of AI ecosystems. Different retailers use different AI models, feed structures, and checkout flows. For a brand to succeed, it must be able to orchestrate its presence across these disparate platforms. This is where infrastructure becomes the ultimate competitive advantage. Companies that can provide a unified view of performance across multiple AI-driven networks will hold a significant edge over those forced to manage each channel in a silo.
The Next 18 Months: A Pivot to Monetization
While much of the current activity involves using AI to support existing workflows, the next wave of innovation will focus on entirely new monetization models. We are likely to see the emergence of "agent-native" ad products—sponsored outcomes that are specifically designed to be surfaced by AI agents based on sentiment, context, and real-time inventory data.
Conclusion: Operating Inside the Shift
The question is no longer whether agentic AI will transform commerce media, but how quickly organizations can adapt their infrastructure to meet the demands of the decision economy.
Koddi, which has spent over a decade building the backend for the world’s largest marketplaces and retailers, is currently operating at the center of this transition. By moving the focus from traditional, static ad placements to dynamic, influence-based systems, they are helping brands bridge the gap between mere visibility and genuine selectability.
As we look toward the future, the divide between companies that understand the mechanics of the decision economy and those that rely on legacy strategies will only widen. Success in this new era will not go to those who automate the most, but to those who create the most effective frameworks for human and AI collaboration. The infrastructure of commerce media has been fundamentally rewritten; the winners will be those who recognize that the shopping journey is no longer a path, but a system.
Dwi Wanna
Iffa Jayyana
