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GenAI for Retail: 26 Use Cases and 21 Brand Success Stories

Discover how leading retailers are using GenAI to innovate faster, personalize experiences, and optimize everything from product design to customer service.

Learn how to build a scalable, future-ready AI strategy through real-world case studies powered by IBM Watsonx.

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With the growing range of GenAI use cases in the retail industry, it’s clear that we are witnessing more than a mere incremental technological advancement. The path ahead points to even deeper integration of artificial intelligence capabilities into every layer of the retail value chain.

Forward-thinking brands like Hugo Boss, L’Oréal, Nike, and Amazon are already moving beyond siloed applications to create unified AI strategies that drive innovation and customer engagement across their entire operations.

Success stories from:

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What will you learn from this e-book?

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Generative AI has a massive economic impact on retail

GenAI could unlock $240-390 billion in economic value for retailers, representing a potential industry-wide margin increase of 1.2-1.9 percentage points. The global AI in retail market is projected to reach $45.74 billion by 2032.

Why generative AI adoption matters for retail

Implementing generative AI isn’t just about following trends – it’s a matter of strategic survival. With GenAI, companies can reduce manual effort, speed up decision-making, and personalize customer experiences at scale, driving both efficiency and growth.

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GenAI helps retail businesses keep up with customer preferences

Consumer behavior is shifting rapidly: 80% of non-AI users express interest in using AI for shopping, 40% leverage generative AI search engines for purchases, and 57% want virtual try-on capabilities before buying.

Democratization of AI capabilities empowers organizations

AI tools are becoming more accessible to retailers of all sizes, moving beyond enterprise organizations. This means anyone familiar with basic digital tools can interact with it using everyday language. This democratization empowers employees at all levels – from marketing to merchandising – to leverage AI-driven insights and automation without needing deep technical expertise, making innovation a company-wide capability.

Check what’s inside

21 real-world retail examples

Brands worldwide demonstrate the success of GenAI technology in retail: ASOS’s Style Match contributed to 3x profit growth, Under Armour sees 35% higher conversion rates with AI search, Starbucks grew rewards membership by 13% through AI-powered promotions, and Walmart achieved a 30% sales increase with dynamic pricing.

26 applications of GenAI in the retail industry

The e-book covers six major use case categories spanning the entire retail value chain: product development, intelligent product search, customer service, personalized shopping experiences, content generation, and supply chain operations. Beyond core applications, it explores 26 nuanced implementations, including AI-powered packaging design, sustainable materials research, trend prediction, virtual shopping assistants, real-time inventory management, and many more.

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GenAI for Retail: 26 Use Cases and 21 Brand Success Stories

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    GenAI technology in retail

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    Faster product development

    Generative artificial intelligence is redefining product innovation in retail, turning guesswork into precision. By rapidly analyzing customer feedback, market trends, and sales data, it uncovers hidden opportunities and sparks smarter ideas. Research timelines shrink from weeks to days, empowering retailers to craft products that resonate with their customers.

    Smarter search

    Search abandonment has become an industry-wide issue because traditional search tools can’t keep up with how people shop today. Generative AI models change that: they interpret natural language, grasping context and customer intent, so shoppers get relevant results, not frustration.

    Customer service

    GenAI is at the front line of customer support. It can handle up to 80% of routine customer queries, enabling faster, context-aware interactions and helping businesses better understand their client. By promoting self-service and making information easily accessible, AI-powered chatbots reduce reliance on human agents while enhancing user experience.

    Personalized customer experiences

    With 71% of consumers expecting tailored online shopping experiences, retail leaders are meeting this demand by using AI-driven tools like personalized recommendations, targeted promotions, dynamic pricing, product customization, and virtual try-ons. These technologies tailor the shopping journey, boosting customer engagement, satisfaction, and ultimately sales.

    Content generation

    Generative AI solutions empower retailers to produce high-quality content at scale. They can reduce content creation time by half and improve content quality by 30%. Whether it’s product descriptions, social media posts, or marketing campaigns, AI ensures consistency across channels, adapts to brand voice, and frees up teams to focus on strategy and creativity.

    Supply chain management

    Inventory distortion costs the retail industry over $1.7 trillion globally, with out-of-stocks and overstocks draining revenue. With real-time visibility from warehouse to shelf, AI optimizes stock levels, automates the procurement process, and ensures products flow efficiently to minimize waste and maximize availability.

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    Radek Grebski

    Radosław Grębski

    CTO
    Leading Neontri’s technology strategy, Radek oversees advanced AI projects, cloud architecture, and long-term product strategy. He pairs deep engineering expertise with strong business insight to turn complex technology into practical, high-impact solutions for clients and users.