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Where retailers are using AI now
A National Retail Federation (NRF) survey conducted in summer 2025 asked 56 AI leaders at U.S.-based retailers about their organizations’ use of AI. The results, published December 17, 2025, point to a concentration in internal work and risk management rather than a uniform shift across every retail function.
| Area | NRF survey finding | What it indicates |
|---|---|---|
| IT coding and app development | 75% of surveyed retailers said they were implementing AI in this area. | AI is being applied to employee-facing technology work, including software development. |
| Office productivity | 73% said they were implementing AI in office productivity tools. | Adoption also reaches general work tasks, not just customer-facing systems. |
| Cybersecurity and fraud prevention | 66% said they were implementing AI in this area. | Retailers are using AI in security and risk-related work as well as productivity. |
These percentages describe the surveyed U.S. retail AI leaders’ reports, not all retailers or independently verified deployment. They show where respondents said implementation was concentrated at that time; they do not measure how much each system improved performance.
What retailers say they plan to prioritize
The same NRF survey asked about future AI priorities. Supply chain operations were identified by 59% of respondents, and marketing and advertising by 45%. These are stated priorities, not evidence that those uses were already widely deployed or that planned projects were completed.
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Respondents most often named IT application development (50%) and customer personalization (48%) as areas where they saw the strongest returns. Those are retailers’ reported assessments, not audited causal outcomes. The figures do not prove that AI alone produced a particular increase in sales, profit, conversion or productivity.
How AI is entering the shopping journey
For shoppers, AI is becoming an additional channel for product discovery and evaluation. In research published January 7, 2026, NRF and IBM reported findings from proprietary research involving 18,000 consumers globally: 41% said they use AI assistants to research products, 33% to look for reviews and 31% to search for deals. These are separate reported activities; they should not be read as the share of shoppers who complete purchases through an AI assistant.
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Adobe’s 2026 AI and Digital Trends overview, based on global surveys conducted by Oxford Economics in partnership with Adobe from October through November 2025, says one in four shoppers turn to AI-powered platforms ahead of brand websites when making purchase decisions. The study surveyed 4,000 customers and 3,000 executives and practitioners globally; retail and consumer goods respondents made up 17% of the executive and practitioner group. The finding signals that some shoppers consult AI platforms before a retailer’s own site, but it is not a measure of purchases displaced from those sites.
Deloitte’s Q1 2026 retail and consumer trends report says 23% of consumers use generative AI for product discovery while shopping. That measure comes from a separate research program, so it is not directly comparable with NRF/IBM’s assistant-use figures or Adobe’s finding about where shoppers turn for purchase decisions.
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Discovery, comparison and personalization
AI assistants can act as a layer between a shopper and a retailer’s catalog: a consumer may start by asking for product ideas, seek reviews or look for a deal instead of beginning with a brand’s search box. Retailer-side personalization is a related but different use. It tailors an experience using information a retailer has about a customer, while an outside AI platform may influence what products a shopper considers before reaching a retailer.
NRF respondents’ reported returns in customer personalization suggest retailers see value in that work, but the survey does not quantify how much personalization changed an individual shopper’s experience or caused additional sales.
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Shopping agents and in-chat commerce are emerging
Some retail experiences are moving from AI-assisted search toward assistants that may help shoppers take actions within a conversation. Deloitte describes in-chat shopping partnerships and notes the growing importance of structured product data: product details need to be organized in ways that AI systems can interpret and present. Retailers therefore face decisions about how to make catalog information available to third-party AI services while maintaining control over accuracy and the customer relationship.
Amazon’s company-authored account says its shopping assistant Rufus was renamed Alexa for Shopping on May 13, 2026. That is a vendor-reported product change, not evidence that all retailers or shopping platforms offer equivalent capabilities. Product availability and functionality can vary over time and by market; Amazon’s own descriptions and usage metrics should be treated as company claims rather than independent industry-wide measurements.
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Convenience depends on trust and governance
Consumer interest does not eliminate concerns about how shopping data is used. In the NRF/IBM consumer research, 52% of consumers said they were comfortable sharing data, while 83% reported overlapping concerns about privacy, misuse and unwanted marketing. The figures can coexist: someone may accept sharing information for a useful service and still worry about how that information could be handled or used later.
NRF and PwC’s March 19, 2026 report on managing and governing agentic AI in retail draws on late-2025 workshops with U.S. retail cybersecurity, technology, legal and business leaders. It frames governance and security as foundations for retail AI deployments, including agentic commerce. For retailers, that means treating access controls, data handling and oversight as part of the system design, not as an afterthought once an AI shopping feature is live.
What the evidence does—and does not—show
Taken together, the available findings show AI spreading across employee tools, IT development, fraud prevention, personalization and online product discovery. They also show that AI-mediated shopping and agentic commerce are developing channels rather than settled replacements for retailer websites.
- Survey findings: NRF’s retailer figures describe reports from 56 U.S.-based retail AI leaders surveyed in summer 2025. NRF/IBM, Adobe/Oxford Economics and Deloitte report separate consumer findings gathered through different research programs.
- Company product claims: Amazon’s account describes its own product and should not be treated as an independent comparison of shopping assistants.
- No single net-impact estimate: These sources do not establish a causal, retail-wide estimate of AI’s effect on revenue, costs, productivity or employment. Reported adoption, perceived returns and consumer usage answer different questions.
For shoppers, the practical change is that product discovery and comparison can begin outside a retailer’s own website. For retailers, the change is broader: AI is being applied to internal work and security as well as to the customer journey, while data quality, privacy and governance shape how far those uses can responsibly go.
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