For decades, retailers optimized the moment of purchase, store layout, pricing strategy, promotions, and checkout efficiency. The latest study from IBM and the National Retail Federation makes one thing unambiguously clear: that moment now begins much earlier, and increasingly, it begins with AI.
The IBM–NRF research captures a structural shift in consumer behavior. Artificial intelligence is no longer an auxiliary shopping aid; it is becoming a primary filter through which consumers interpret value, relevance, and trust, often before they visit a store or open a brand’s app.
The Silent Rewiring of the Pre-Shopping Phase
Physical retail is far from obsolete. Nearly three-quarters of consumers still shop in stores. However, the path that leads them there has changed fundamentally. According to the study, 45% of consumers now consult AI tools during their shopping journey, especially for product research, checking reviews, and for deals. 41%, interpret reviews 33%, and find deals 31%.
This matters because the pre-shopping phase, once fragmented and informal, is now structured and data-driven.
AI systems influence consumer decisions about which products they consider, which brands they trust, and which price feels reasonable. For retailers, this means loss of control over the earliest.
From Search Tool to Decision Partner
Consumers are no longer using AI merely to retrieve information; they are delegating judgment.
AI tools analyze thousands of reviews, compare alternatives, and recommend the best options based on your preferences and context.
AI is now acting as a proxy decision-maker, reducing cognitive effort for consumers while quietly redefining brand competition.
The study shows this momentum across sectors, from fashion and electronics to grocery and everyday consumer goods. Here, brands are not competing with each other, but they are competing for AI visibility and algorithmic preference.
The Readiness Gap Inside Retail Organizations
Consumer adoption of AI tools is rising while retail organizations struggle to keep pace. The research highlights internal challenges like fragmented data systems, inconsistent product information across channels, and a lack of AI expertise.
The study shows that 35% of consumers value visually appealing stores and prefer no wait time.
The gap is critical. AI systems’ effectiveness depends on data quality. Poor product metadata, pricing inconsistencies, or outdated inventory information undermine the quality of AI-driven consumer interactions. Inaccurate AI guidance erodes trust quickly, and trust, once lost, is difficult to regain.
Traditional Retail Excellence Is No Longer Enough?
The study does not undervalue the importance of in-store experience. 72% of consumers still visit stores in person, which indicates that physical experience remains relevant.
In practical terms, this means that brand strategy, product storytelling, and differentiation must be optimized not only for humans but for machines that interpret and present those narratives.
The IBM–NRF research establishes that AI is no longer peripheral in retail strategy; it is central to how consumers discover, evaluate, and decide on purchases.
To view the full study, visit: https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/agentic-commerce.
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