Generative AI in Retail: Transforming Customer Experience, Supply Chain, and E-Commerce

Generative AI is rapidly reshaping the retail landscape, unlocking new opportunities for growth, efficiency, and customer engagement. As leading retailers like Walmart, Amazon, and eBay demonstrate, the adoption of generative AI is no longer a futuristic ambition—it's a present-day imperative. At Publicis Sapient, our retail and AI experts are at the forefront of this transformation, helping clients harness the power of generative AI to deliver differentiated experiences, optimize operations, and build lasting customer trust.

The Generative AI Revolution in Retail

Generative AI refers to advanced artificial intelligence models capable of creating new content—text, images, code, and more—based on vast datasets. Unlike traditional automation, generative AI brings a new level of creativity and contextual understanding, enabling retailers to move beyond static rules and manual processes. The result? More personalized, efficient, and engaging retail experiences across the value chain.

Key Areas of Impact

Customer Experience & Conversational Commerce
- Conversational Product Search: Generative AI is redefining how customers interact with online stores. Instead of relying solely on keyword-based search, shoppers can now use natural language to describe what they want—"Show me a summer outfit for a beach vacation"—and receive tailored recommendations. This shift accelerates product discovery, increases conversion rates, and boosts average basket sizes.
- AI-Powered Chatbots: Modern chatbots, powered by generative AI, go far beyond scripted responses. They can handle complex queries, provide personalized advice, and even mirror a brand’s unique tone of voice. Retailers are using these bots to resolve customer issues, recommend products, and drive upsell opportunities—all while reducing the burden on human support teams.
- Hyper-Personalized Marketing: By analyzing customer data and generating individualized content, generative AI enables retailers to deliver marketing messages that resonate on a personal level. From dynamic email campaigns to real-time deal alerts, the technology helps brands cut through the noise and foster deeper loyalty.
Automated Content Generation & E-Commerce Operations
- Product Descriptions and Reviews: Retailers, especially marketplaces, face the challenge of inconsistent product information from third-party sellers. Generative AI can automatically standardize product descriptions, ensuring accuracy, brand alignment, and SEO optimization. Amazon, for example, uses AI to summarize customer reviews, making it easier for shoppers to make informed decisions.
- Personalized Product Imagery: AI-generated images allow retailers to showcase products in diverse contexts, tailored to individual customer profiles. Imagine seeing a sneaker displayed on a digital twin that matches your own style and environment—this level of personalization is now within reach.
- Streamlined Transaction Flows: Generative AI can auto-fill forms, guide vendors through onboarding, and create customized landing pages, reducing friction and accelerating the path to purchase.
Supply Chain Optimization
- Enhanced Visibility and Decision Support: Generative AI adds a conversational layer to supply chain management. Stakeholders can ask, “Where is my package?” or “Can this shipment be rerouted?” and receive instant, accurate answers. This reduces manual effort and improves transparency.
- Dynamic Packing and Labeling: AI can suggest optimal packing configurations or generate new shipping label layouts on the fly, accommodating unique constraints and minimizing errors.
- Forecasting and Secondary Decision-Making: By integrating with existing prediction algorithms, generative AI can provide scenario-based recommendations, helping supply chain leaders respond to disruptions or changing demand patterns with agility.

Real-World Examples from Leading Retailers

Walmart: Rolled out "My Assistant," an internal generative AI tool that helps associates with tasks like summarizing documents and answering HR questions, boosting productivity and freeing up time for higher-value work.
Amazon: Uses AI to generate concise summaries of product reviews, distilling thousands of customer opinions into actionable insights for shoppers.
eBay: Employs generative AI to create product descriptions from seller-uploaded photos, streamlining the listing process and improving consistency across the marketplace.

Practical Advice for Retail Leaders

1. Start with Data Strategy

Generative AI’s effectiveness depends on the quality and breadth of your data. Invest in centralizing customer, product, and operational data, and establish robust governance to ensure privacy, security, and compliance. The more structured and accessible your data, the greater the ROI from AI initiatives.

2. Pilot High-Value, Low-Risk Use Cases

Begin with areas where generative AI can deliver quick wins—such as conversational search or automated content generation—before scaling to more complex applications. Use pilots to build internal expertise, measure impact, and refine your approach.

3. Prioritize Ethical AI and Customer Trust

Transparency is critical. Clearly communicate when customers are interacting with AI, and ensure your models are free from bias and hallucinations. Develop and enforce ethical guidelines, and stay ahead of evolving regulations like the EU AI Act. Walmart’s public Responsible AI Pledge is a strong example of leadership in this area.

4. Upskill Your Workforce

AI is a tool for augmentation, not replacement. Equip your teams with the skills to leverage generative AI, from prompt engineering to data stewardship. Foster a culture of experimentation and continuous learning.

5. Plan for Scalability and Integration

As pilots succeed, plan for enterprise-wide adoption. Integrate generative AI with your existing platforms—CMS, supply chain, CRM—and ensure your technical architecture can support future growth.

Navigating Risks and Opportunities

Data Quality and Security: Poor data leads to poor outcomes. Invest in data hygiene and secure, compliant infrastructure.
Customer Trust: Misuse or lack of transparency can erode trust. Be clear about AI’s role and limitations.
Regulatory Compliance: Stay informed about global AI regulations and ensure your practices are up to date.
Shadow IT and Siloed Efforts: Coordinate AI initiatives across the organization to avoid duplication and security gaps.

The Road Ahead: Generative AI as a Retail Differentiator

The initial hype around generative AI is giving way to practical, value-driven adoption. In the coming years, generative AI will become a cornerstone of retail innovation, powering everything from hyper-personalized shopping journeys to autonomous supply chain operations. Retailers that invest now—in data, talent, and ethical frameworks—will be best positioned to lead.

At Publicis Sapient, we combine deep retail expertise with cutting-edge AI capabilities to help clients navigate this transformation. Whether you’re exploring your first pilot or scaling enterprise-wide, our SPEED approach—integrating strategy, product, experience, engineering, and data—ensures you achieve measurable business outcomes, responsibly and at pace.

Ready to unlock the next era of retail? Connect with our retail and AI leaders to start your generative AI journey.