Retail’s AI Commerce Inflection Point

Retail and consumer packaged goods companies are entering a new phase of digital commerce, one increasingly influenced by artificial intelligence systems that act on behalf of shoppers rather than simply responding to them.

These systems, often described as agentic AI, are designed to coordinate parts of the shopping journey that once required direct consumer involvement. They can search for products, compare options, evaluate price and availability, and in some cases complete transactions after limited user confirmation. While adoption is still emerging, the direction is clear enough that retailers are already adjusting strategy.

Over the past year, several large retailers, including Walmart, Target, and Etsy, have expanded partnerships that make their product assortments accessible through AI platforms such as OpenAI’s ChatGPT, Google’s Gemini, and Microsoft Copilot. At the same time, retailers including Amazon and Walmart continue investing heavily in their own AI assistants, signaling that control over AI-driven discovery and commerce is becoming strategically important.

What differentiates this moment from earlier digital shifts is not simply where transactions occur, but who influences decisions before a purchase ever happens.

From AI Assistance to AI Action

Retailers have used AI for years to support forecasting, personalization, and operational efficiency. The current shift goes further. AI systems are beginning to anticipate intent and initiate actions rather than waiting for explicit instructions.

This transition has been reflected in recent industry research. Deloitte’s 2026 retail outlook found that many retail executives expect the traditional, multi-step shopping journey to compress over the next few years as AI systems handle more of the discovery and decision process. McKinsey has similarly characterized agentic AI as a structural change, with the potential to reshape how consumers and businesses interact across end-to-end workflows.

At the National Retail Federation’s 2026 Big Show, AI discussions reflected this change in tone. Executives focused less on experimentation and more on how AI capabilities are being embedded across merchandising, marketing, supply chains, and store operations. AI was increasingly described as a core business capability rather than a digital add-on.

Consumer behavior is beginning to follow. Adobe reported that traffic to U.S. retail websites originating from AI-driven sources increased nearly sevenfold year over year during the 2025 holiday season. While AI-generated traffic still represents a relatively small portion of total e-commerce volume, the growth rate has drawn attention from retailers concerned about future visibility and relevance.

Data, Visibility, and Control

As AI agents take on a larger role in shopping journeys, data ownership becomes a central issue.

In traditional e-commerce, retailers capture detailed insight into shopper behavior, including search terms, product views, comparisons, and cart activity. These signals inform assortment decisions, marketing investments, and personalization strategies. When discovery and decision-making occur inside external AI platforms, much of that context may not flow back to the retailer in full.

Deloitte’s research suggests this concern is widely shared. A significant majority of retail executives surveyed believe generative AI could weaken brand loyalty in the near term. The issue is not brand irrelevance, but reduced differentiation when choices are filtered through algorithms optimized for efficiency, relevance, and price.

Technology platforms emphasize collaboration and data sharing, and many are building tools to support retailer participation. Still, even partial loss of visibility can limit a retailer’s ability to understand why a product was selected, what alternatives were considered, and how preferences are evolving over time.

The Risk of Disintermediation

Retailers have navigated disintermediation pressures before, from search engines to marketplaces to social commerce. Agentic AI raises the stakes because it can remove the customer interface entirely.

If an AI agent automatically replenishes household items, selects apparel based on past preferences, or chooses retailers based on delivery reliability and price history, the brand experience becomes mediated by an algorithm. In that environment, retailers risk being evaluated primarily on operational performance rather than storytelling, emotional connection, or loyalty programs.

This helps explain why many retailers are pursuing a dual strategy. Participation in external AI platforms offers reach and relevance, while continued investment in first-party AI experiences helps preserve direct customer relationships. For most retailers, opting out is not realistic. AI platforms are becoming discovery engines, and absence can quickly translate into reduced visibility.

OpenAI has stated that features such as instant checkout may be considered alongside factors like price, availability, and quality when ranking merchants offering the same product. As AI-driven discovery matures, these mechanics are likely to play a larger role in competitive positioning.

A New Kind of Customer

Agentic commerce also changes who retailers are effectively selling to.

In many interactions, the immediate decision-maker is not a human shopper but an AI agent acting on their behalf. These agents prioritize structured product data, consistent availability, transparent policies, and reliable fulfillment. Emotional appeal still matters, but it must be expressed in ways that algorithms can interpret and compare.

Bain & Company research indicates that while many consumers remain cautious about fully autonomous purchasing, trust builds quickly when AI-assisted interactions consistently deliver positive outcomes. That dynamic places pressure on retailers and brands to ensure their data, content, and operations are optimized for machine-mediated decision-making.

In physical stores, AI’s influence is also becoming more apparent. Shoppers already access reviews, pricing, and alternatives in real time. The difference now is that AI can synthesize that information conversationally and contextually. Some retailers are equipping store associates with AI tools to help them remain credible and effective in these moments, reinforcing rather than replacing the human role.

Strategic Decisions Taking Shape

Agentic commerce is still evolving, but several strategic patterns are emerging.

Retailers and brands are investing in structured, machine-readable product data so AI systems can accurately evaluate and present their offerings. Payment networks and technology providers are working to establish standards for secure, trusted agent-driven transactions. At the same time, questions around data governance, privacy, and reliance on platform ecosystems remain unresolved.

Loyalty strategies are also under review. Programs built around direct engagement may need to adapt as AI agents mediate interactions. Retailers will need new ways to signal value, reliability, and preference when traditional touchpoints are compressed or bypassed.

Agentic commerce is not simply another channel to manage. It represents a shift in how shopping decisions are made and who influences them. The choices retail and CPG leaders make now, around partnerships, data strategy, and internal capabilities, will shape how visible and resilient their organizations remain as AI becomes an increasingly active participant in commerce.

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