Agentic commerce: the new frontier in retail purchasing decisions

The retail landscape is shifting rapidly, driven by a quiet but powerful force: AI agents.

Retail’s new reality: selling to AI agents, not just people

Agentic commerce goes beyond assisting shoppers; it allows AI to make purchasing decisions on behalf of consumers. Increasingly, the next customer a retailer serves may be a digital agent acting in place of a human.

This change transforms the traditional buyer-retailer relationship into a complex, multilayered interaction. AI agents can engage directly with retail websites, negotiate with other agents or operate through brokered platforms linking buyers and sellers. Each channel presents unique challenges and opportunities that retailers must navigate carefully.

One major challenge is maintaining a clear understanding of who the customer really is. When AI agents function as intermediaries, retailers risk losing direct access to valuable insights on preferences, purchase history and behavior. This fragmentation makes it harder to personalize offers and build lasting loyalty.

At the same time, AI agents offer new opportunities to enhance customer engagement. These digital proxies analyze vast amounts of data quickly, enabling smarter product recommendations and more efficient purchasing decisions. Retailers that learn to work effectively with AI agents can tap into emerging trends and better anticipate consumer needs.

The evolving dynamic also calls for a fresh approach to loyalty and trust. Traditional programs rely on direct consumer interaction, but with AI agents involved, retailers must build relationships that extend to these digital representatives. Creating seamless, personalized experiences that resonate through AI agents will be key to strengthening connections with end customers.

Developing an agentic commerce playbook
Adapting to this fast-changing environment requires a clear strategy. Retailers must balance collaboration with third-party AI agents, building proprietary agent experiences that differentiate their brand and investing in the core systems that support these efforts.

Several operational challenges demand attention:
1. First, data reconciliation is critical. Retailers must accurately identify and understand AI agents acting on behalf of customers. Without this clarity, tailoring offers and fostering loyalty becomes difficult.
2. Next, capturing meaningful data from agent interactions is essential. These exchanges provide insights that can shape future shopping experiences, but only if retailers have the tools to collect and analyze the data effectively.
3. Security and accountability also take on new importance. When AI agents manage transactions, verifying payments and managing risks becomes more complex. Retailers must implement strong safeguards to protect their business and customers as this new commerce model takes hold.

Gaining traction across categories
Agentic commerce is reshaping product assortment and retail strategy. AI-driven recommendations influence both in-store and online selections, prompting retailers to rethink how they stock and showcase products. 

Routine purchases, such as household staples, see faster adoption because consumers prioritize convenience and price. In contrast, experiential or luxury goods, such as apparel and perfume, require higher trust and personalization. Shoppers want assurance that AI agents understand their tastes before making decisions.

Brand endorsements and personalized experiences help bridge this trust gap. 

When consumers see trusted names backing AI-driven shopping or receive tailored recommendations that feel authentic, they are more likely to embrace agentic commerce. Retailers investing in these trust-building elements and adapting their infrastructure will be better positioned to capture opportunities this new model offers.

The strategic risk of inaction
Delaying action on agentic commerce carries serious risks. As AI agents take charge of buying decisions, retailers that fail to engage lose control over vital customer data. This loss makes it harder to tailor products and anticipate market trends, weakening their ability to respond to changing preferences.

Third-party AI platforms add complexity by introducing new layers of intermediation. As more transactions pass through these external agents, direct consumer relationships weaken. This shift erodes brand loyalty and limits personalized engagement. Without a clear strategy to work with or compete against these intermediaries, retailers risk becoming mere suppliers.

Margin pressure also intensifies as AI agents prioritize cost efficiency, steering purchases toward lower-margin products or competitors offering better deals. Retailers slow to adapt may see profits shrink amid rising price competition and fading differentiation.

Looking ahead
The future of agentic commerce will be shaped by shoppers who are knowledgeable and comfortable with AI-driven purchasing. These consumers will expect seamless, personalized experiences that align with their preferences while retaining control over buying decisions.

Manufacturers and retailers must also carefully assess the technological ecosystems they choose, navigating a complex landscape with no universal standard. This fragmented environment requires flexibility and adaptability. Businesses need to be prepared to work with a range of AI platforms and intermediaries, each operating with their own protocols and capabilities.

Striking the right balance between AI agent autonomy and consumer oversight will be critical. Shoppers want AI to simplify and speed up the buying process but also want to stay involved in key decisions. Retailers that manage this balance effectively will position themselves as leaders in the evolving world of agentic commerce.
 

Will Auchincloss is EY-Parthenon Americas retail sector leader, John Dubois is EY Americas AI strategy leader and Don K. Johnson is principal, strategy and execution, EY-Parthenon, Ernst & Young LLP.