Deloitte/WSJ Analysis: 68% of Retail Executives Plan Agentic AI Deployment as AI Becomes the Buyer

Deloitte Analyzes Agentic Commerce Impact via WSJ

When AI Becomes the Buyer: How Agentic Commerce is Reshaping Retail

As AI agents play a bigger role in the path to purchase, retailers anticipate shifts in brand dynamics and enterprise operations

deloitte.wsj.com

On April 1, 2026, Deloitte published an analysis on The Wall Street Journal examining how retail is changing as AI agents take on the role of buyer. Brian McCarthy, a principal with Deloitte Consulting LLP, states that "with the advent of agentic commerce, AI agents can find products, compare options, make decisions, and complete transactions with very little human involvement."

The analysis is based on a Deloitte survey of 330 senior retail executives. According to the findings, some retailers are already seeing 15% to 20% of referral traffic coming from AI chat interfaces rather than traditional search or apps.

Why "AI as the Buyer" Matters

The essence of agentic commerce lies in the structural shift of consumer purchasing processes toward AI-mediated paths. McCarthy notes that "the steps consumers take today will likely compress into a more direct, AI-mediated path from intent to purchase."

This change is not simply an addition of a new channel but a fundamental transformation of the buying journey. Deloitte's research shows that 63% of global retail leaders acknowledge that companies without AI agents will lose competitiveness within two years. Furthermore, 58% believe AI agents will handle most customer interactions within five years.

McKinsey projects the agentic commerce market will reach $1 trillion in the U.S. alone by 2030. The era where purchase decisions are delegated to AI is no longer a future scenario but a present reality.

Brand Strategy and Data Readiness Become Urgent

A particularly notable finding is that a large majority of executives expect agentic commerce to influence brand dynamics as purchase decisions become more automated and data-driven. AI agents prioritize "data accuracy," "pricing transparency," and "real-time inventory" over "brand recognition" when selecting products.

McCarthy states plainly: "In an agent-driven environment, accuracy, timeliness, and structure determine whether products show up." In other words, traditional brand power alone no longer guarantees inclusion in AI agent recommendation lists.

To address this challenge, a new optimization strategy called "SEO to GEO (Generative Engine Optimization)" is gaining attention in the retail industry. GEO involves structuring product data and optimizing content to be discovered and recommended by AI agents. Gartner predicts that organic traffic from traditional search engines will decline 25% by 2026, underscoring the urgency of GEO adoption.

Expanding Into Enterprise Operations

The impact of agentic AI extends beyond customer touchpoints. 68% of survey respondents expect to deploy agentic AI for key operational and enterprise activities within 12 to 24 months, including pricing, demand forecasting, customer service, and marketing.

Bain & Company's analysis outlines a five-stage evolution model for AI agent development. The progression moves from current "assisted discovery" through "agentic shopping" to the eventual "agent-to-agent commerce." Deloitte identifies building agent-compatible data infrastructure and APIs, along with establishing trust and governance protocols, as key priorities for this evolution.

Impact and Applications for E-Commerce Businesses

McCarthy concludes that "in 2026, agentic commerce presents real implications and real opportunities." There are three immediate actions e-commerce businesses should prioritize.

Structuring and improving data accuracy: Making product information, pricing, and inventory data easily readable by AI agents is the top priority. Siloed data systems risk products being excluded from AI recommendations.

Developing a GEO strategy: Beyond traditional SEO, optimization for AI-driven product discovery is essential. This requires comprehensive structured data, complete attribute information, and clear operational signals such as shipping speed and return policies.

Considering proprietary agents: According to Deloitte's guide, building branded agents and tracking performance metrics is a strategic priority. Rather than relying solely on third parties, providing agent experiences that leverage proprietary expertise creates meaningful differentiation.

Conclusion

The Deloitte/WSJ analysis demonstrates that agentic commerce is simultaneously transforming both "customer touchpoints" and "enterprise operations" in retail. Companies that engage early will have greater influence over how AI agents shape purchasing decisions.

The key factor to watch is the pace at which Deloitte's five-stage evolution model progresses. In particular, developments around Google's Universal Commerce Protocol (UCP) and Microsoft's agentic commerce APIs will serve as important indicators shaping industry standards.