Brands, Retailers Navigating a New Reality as AI Shapes Consumer Decisions Before Shopping Begins: IBM-NRF Study
Armonk, NY (Jan. 7, 2026) – Generative AI is reshaping the first steps of our shopping experience before we ever click “buy.” From hyper-personalized suggestions to curated inspiration, influence now begins long before a store visit or app tap, moving where brands and retailers compete to an entirely new level.
A new global study* from the IBM Institute for Business Value, in collaboration with the National Retail Federation (NRF), found that while nearly three-quarters of surveyed consumers (72%) still shop in stores, almost half (45%) turn to AI for help during their buying journeys. Shoppers still want to see and touch products, but today’s savvy consumers increasingly arrive with a sense of what they’re looking for and why. They are using AI to research products (41%), interpret reviews (33%), and hunt for deals (31%).
“AI is changing how consumers shop, and every aspect throughout the shopping journey,” notes Caroline Reppert, Senior Director, AI and Technology Policy at the National Retail Federation, “As these technologies increasingly guide consumer discovery, comparison, and choice, retailers that understand and respond to this shift will be best positioned to earn trust, relevance, and long-term customer loyalty.”
From browsing to guided buying: How AI is shaping choices
For leading brands and retailers, this shift toward AI-shaped discovery is prompting a rethink of how and where they engage consumers.
As Matthieu Houle, CIO at ALDO Group, explains, “AI is turning shopping into a trusted conversation, much more than a search. Consumers now rely on assistants that feel almost human, know their preferences, and offer neutral, best-for-me advice that reshapes how they validate and decide what to buy.”
While 35% of surveyed consumers still desire visually appealing stores with no wait times, AI-powered solutions are nearly as important. In fact, one in three consumers seek super apps that combine commerce with other services, 30% want smart homes with AI personal shoppers and autonomous delivery, and 29% look for effortless purchasing through social platforms.
Consumers are growing increasingly accustomed to AI-powered shopping assistants helping them decide what to buy. That expectation, however, is forming faster than most retail operating models can keep pace, forcing the question: Is our data ready to guide and validate what customers ultimately choose?
“AI is not a magic wand,” emphasizes Stanislas Vignon, Head of Insights (AI and Omnichannel) at Louis Vuitton Moët Hennessy (LVMH), “If you don’t have the right data, it doesn’t work. And you must test your solution to know whether it works and where it will bring value.”
How brands and retailers can stay ahead of AI-driven consumers
As AI transforms how consumers make choices, brands and retailers need to anticipate change and intentionally design experiences that meet shoppers where they are, with focus on:
- Redesign the journey around future decision moments. Identify where consumers will use AI to research, compare, and look for value, and ensure those moments connect seamlessly to purchase.
- Use agents to reduce uncertainty earlier in the journey. Put deal-hunting, review interpretation, and personal shopping support where it will help consumers decide, not only where it deflects service volume.
- Make data readiness and testing non-negotiable. With more than half of surveyed brand executives (54%) reporting persistent challenges across channels and systems, aligning product and policy truth and testing end-to-end is essential.
- Amplify what makes the brand distinctive. Use AI to scale relevance and remove friction while preserving creativity and authentic brand expression.
- Invest in AI skills and partnerships. More than half of executives (51%) cite limited AI expertise, underscoring the need to strengthen internal capabilities while partnering strategically to scale AI responsibly and effectively.
AI is reshaping where, when, and how decisions are made across every industry. In retail, understanding AI-influenced consumer behavior will become a defining competitive advantage, separating brands and retailers that shape decisions from those that simply fulfill them.
To view the full study, visit: https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/agentic-commerce.
Study methodology
To examine how consumers and business leaders are preparing for AI-enabled shopping and agentic commerce, the IBM Institute for Business Value conducted two global surveys in Q3 2025: one of consumers and one of industry executives. The consumer survey included over 18,000 respondents from 23 countries, representing diverse shopping behaviors. The executive survey gathered insights from 200 senior leaders across retail, consumer goods, and e-commerce organizations. Respondents were segmented by engagement style, price sensitivity, and AI-related knowledge. Descriptive analyses identified key patterns, and validated statistical techniques were applied to compare priorities and assess trust-focused engagement strategies.
About IBM
IBM (NYSE: IBM) is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. More than 4,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity and service. Visit www.ibm.com for more information.
Source: IBM
Tags: Artificial Intelligence (AI), Customer Journey Mapping (CJM), IBM