Generative AI in Retail: From Conversational Commerce to Automated Content Creation

Generative AI is rapidly redefining the retail landscape, moving beyond traditional product recommendations to power a new era of conversational commerce, automated content creation, and hyper-personalized customer journeys. As leading retailers and marketplaces like Amazon and eBay deploy generative AI at scale, the technology is proving its value across both customer-facing and back-end operations—driving efficiency, unlocking new revenue streams, and transforming the way brands engage with shoppers.

The Expanding Role of Generative AI in Retail

At its core, generative AI refers to artificial intelligence models capable of creating new content—text, images, code, and more—based on large datasets. In retail, this means AI can now generate product descriptions, summarize customer reviews, create personalized marketing assets, and even power natural language search and chat experiences. The result is a more dynamic, responsive, and scalable retail operation that meets the evolving expectations of today’s digital-first consumers.

Conversational Commerce: Meeting Shoppers Where They Are

One of the most visible impacts of generative AI is in the realm of conversational commerce. Retailers are leveraging advanced AI models to:

Enhance product search: Generative AI enables shoppers to interact with search bars and chatbots in natural language, asking complex questions or searching for entire outfits, recipes, or bundles in a single query. This not only accelerates product discovery but also increases conversion rates and average basket sizes.
Power intelligent chatbots: Unlike traditional chatbots limited by rigid decision trees, generative AI-driven bots can engage in nuanced, brand-aligned conversations, resolving customer queries, guiding product selection, and even handling returns or order tracking with greater empathy and accuracy.
Drive cross-sell and upsell: By analyzing customer behavior and preferences, generative AI can suggest complementary products or next-best actions in real time, increasing order value and deepening customer engagement.

Recent consumer research shows that shoppers are not only open to these AI-powered experiences—they’re excited by them. Over a quarter of shoppers express enthusiasm for generative AI’s ability to improve real-time price comparison, deal alerts, and search results, while 25% would use a virtual AI shopping assistant if available.

Automated Content Creation: Scaling the Digital Shelf

Generative AI is also revolutionizing the back-end of retail by automating content creation at scale:

Product descriptions: Marketplaces like eBay now use generative AI to automatically generate comprehensive, standardized product descriptions from seller-uploaded photos and minimal input. This reduces manual effort, ensures consistency, and improves SEO and conversion.
Review summarization: Amazon’s AI-generated review summaries distill thousands of customer reviews into concise, actionable insights, helping shoppers make informed decisions quickly and reducing the impact of review fraud.
Personalized imagery and creative: AI can generate tailored product images or marketing assets based on customer segments, preferences, or even individual profiles, enabling more relevant and engaging campaigns without the need for extensive creative resources.
Auto-filled transaction flows: Generative AI can dynamically adapt web pages and checkout flows to individual users, streamlining the purchase journey and reducing friction.

These capabilities not only drive operational efficiency but also free up human teams to focus on higher-value, strategic work.

Beyond the Front End: Generative AI in Supply Chain and Operations

The impact of generative AI extends deep into retail operations:

Supply chain optimization: Generative AI can serve as a conversational interface for supply chain managers, answering complex queries like “Where is my package?” or “Can this shipment be rerouted?” in real time, drawing on data from multiple systems.
Decision support: AI can assist with secondary decision-making, such as optimizing packing configurations or generating new shipping label layouts based on unique constraints, reducing errors and accelerating response times.
Employee productivity: Retailers like Walmart are deploying generative AI-powered assistants to help employees summarize documents, take meeting notes, and access HR information, streamlining internal workflows and knowledge sharing.

Real-World Examples: Industry Leaders Setting the Pace

Amazon: AI-generated review summaries help customers quickly understand product pros and cons, while reducing the risk of fraudulent reviews.
eBay: Automated product description generation for third-party sellers accelerates listing creation and improves the quality of marketplace content.
Walmart: Internal generative AI tools like “My Assistant” support employee productivity, and the company has established public guidelines for ethical AI use.

These examples illustrate how generative AI is already delivering measurable ROI—improving customer experience, reducing costs, and enabling new business capabilities.

Implementation Roadmap: Laying the Foundation for Success

While the promise of generative AI is immense, successful implementation requires a thoughtful, data-driven approach:

Invest in data strategy: Generative AI models are only as good as the data they’re trained on. Retailers must centralize and govern customer, product, and operational data to ensure quality, privacy, and compliance.
Start with high-impact use cases: Conversational commerce and automated content creation are ideal entry points, offering quick wins and valuable learning opportunities.
Upskill teams: Equip associates and content creators with the skills to work alongside AI, from prompt engineering to ethical oversight.
Modernize technical architecture: Legacy systems may need to be reimagined to support AI-driven workflows, including integration with CMS, supply chain, and customer data platforms.
Prioritize transparency and trust: Clearly communicate when customers are interacting with AI, and establish robust policies for ethical AI use and data privacy.

The Publicis Sapient Advantage: A Partner for AI-Driven Retail Transformation

Publicis Sapient stands at the forefront of generative AI in retail, combining deep industry expertise with proven SPEED capabilities—Strategy, Product, Experience, Engineering, and Data & AI. Our teams have helped global retailers and brands:

Launch AI-powered conversational commerce and clienteling solutions
Automate product content and review management at scale
Integrate generative AI into supply chain and operational workflows
Build robust data strategies and ethical AI governance frameworks

As a recognized leader in generative enterprise services, Publicis Sapient partners with clients to design, test, and scale AI solutions that deliver measurable business value—while ensuring transparency, compliance, and a relentless focus on customer experience.

The Future: Generative AI as a Retail Growth Engine

The initial hype around generative AI is giving way to a new reality: in the coming years, this technology will become a cornerstone of profitable, customer-centric retail. Retailers that invest now—in data, talent, and ethical AI practices—will be best positioned to capture new sources of value, drive sustainable growth, and deliver the seamless, personalized experiences that today’s shoppers demand.

Ready to explore how generative AI can transform your retail business? Connect with Publicis Sapient to start your journey toward AI-driven retail excellence.