
Like many other industries, AI is shaking up the e-commerce industry as well. In 2025, we can anticipate a significant transformation in the e-commerce industry due to AI. We conducted case studies to explore how AI is reshaping the e-commerce industry and to identify the anticipated challenges. Here are some case studies of AI in e-commerce.
How AI Is Revolutionizing E-Commerce in 2025: Case Studies from Google, Amazon, and More
At Google I/O 2025, Google introduced AI Mode, a shopping experience powered by Gemini and the Shopping Graph, which now includes over 50 billion product listings from global and local retailers. AI Mode offers a browsable panel of personalized images and listings, dynamically updating based on user preferences. For example, searching for a “cute travel bag” for a trip to Portland, Oregon, triggers simultaneous searches to recommend waterproof bags with accessible pockets, tailored to rainy weather and travel needs.
Amazon
Amazon heavily invests in areas like machine learning, robotics, and computer vision. The e-commerce giant Amazon uses AI technology in different departments.
- Research and Development
- Marketing and Advertising
- Product Development
- Fraud Detection
- Inventory Management
- Supply Chain and Logistics
Amazon's Website and App use AI algorithms to improve product search and recommendations. Alexa and voice assistants use AI to understand users' requests, speech recognition, and natural language processing. Amazon relies on AI-powered chatbots for customer inquiries and resolves issues within a quick period. Last year, Cyber Monday was one of the biggest shopping days, Amazon employed AI to deliver orders even faster. Amazon is actively developing and deploying AI-powered shopping assistants, such as Alexa, and its integration with physical stores like Amazon Go.
Amazon is using AI in almost everything it does. (Source : Youtube Channel : CNN)
Amazon announces Rufus, a new generative AI-powered conversational shopping experience .(Source : Youtube Channel : Amazon News)
Alibaba Group
Alibaba Group and its subsidiary companies are heavily investing and innovating with AI technologies. Alibaba has implemented chatbots for personalized recommendations, automation of Customer Service, and Supply Chain Optimization.
Walmart
Walmart uses conversational AI across several areas of the business to support customers, members, associates, drivers, and marketplace sellers. Walmart's Voice shopping system uses natural language processing (NLP) to identify user requests, products, purchase information, and product name entity recognition. Walmart’s chatbots help customers when they have an issue with their orders. AI-powered Mobile app ‘Ask Sam’ helps Associates by providing answers and emergency alerts in real-time.
eBay
eBay uses AI algorithms for product recommendations, analyzing users browsing history, purchase behavior, and location. eBay's AI-powered Magical listing tool that can generate product listings from just a photo. eBay's new social caption generator AI helps sellers to make social media post sharing more easier.
Stitch Fix
Stitch Fix's AI algorithms generate Product Descriptions and Advertisement Headlines.
Starbucks
The Starbucks app uses AI to recommend drinks to customers based on their past orders, the time of day, and the weather. The app also uses AI for promotions and sales.
Domino's Pizza
Domino's Pizza uses AI to improve its delivery times and customer service. AI-powered features have helped Domino's to reduce its delivery times and improve its customer satisfaction.
Etsy
Etsy leverages AI for Personalized Product Recommendations, Image Search, Fraud Detection and Security, Customer Service, and Product Listing Optimization.
Anticipated Challenges in AI-Driven E-Commerce
Paradigm Shift
Challenge: AI-driven changes demand new business models, disrupting traditional planning and operations.
Solution: Companies must adopt agile strategies and invest in training to adapt to AI-centric workflows.
Data Scale
Challenge: Managing massive datasets, such as Google’s 50 billion product listings or Amazon’s product database, requires robust infrastructure to avoid slowdowns.
Solution: Scalable cloud solutions and AI-driven data processing can handle large-scale data efficiently.
Equitable Access
Challenge: Smaller sellers may struggle to access advanced AI tools, creating competitive disparities.
Solution: Platforms like Google, Etsy, or eBay could provide affordable AI tools or subsidies to ensure inclusivity for smaller vendors.
Innovation Pace
Challenge: The rapid pace of AI advancements, exemplified by Google’s AI Mode and virtual try-on, requires continuous learning and system upgrades.
Solution: Partnerships with AI providers and ongoing training programs can keep businesses competitive.
Internal Implementation
Challenge: Integrating AI into existing workflows, such as adopting Google’s agentic checkout, can disrupt developer productivity.
Solution: Gradual adoption, user-friendly AI tools, and developer training can ensure seamless integration.
Responsible AI
Challenge: Ethical concerns, including bias and fairness, are critical to maintaining trust in AI systems. For instance, biased recommendations or unfair pricing can alienate users.
Google I/O Context: Google’s virtual try-on technology, showcased at I/O 2025, emphasizes responsible AI by using a custom image generation model that preserves clothing nuances across diverse body types. This addresses fairness by ensuring accurate representations for varied users, mitigating bias in virtual fitting experiences. Google’s broader AI efforts, as highlighted at I/O, likely include frameworks to audit and reduce bias, aligning with ethical AI practices.
Solution: Transparent AI models, regular bias audits, and adherence to ethical guidelines are essential for trust and fairness in e-commerce applications.
Conclusion
AI is transforming e-commerce through personalization, automation, and innovative features like Google’s AI Mode and virtual try-on, alongside advancements from Amazon, Alibaba, and others. Google’s I/O 2025 announcements, including the Shopping Graph’s 50 billion listings and agentic checkout, enhance the shopping experience with real-time data and seamless purchasing. However, challenges such as data scale, equitable access, and ethical AI use require proactive solutions. By addressing bias in tools like virtual try-on and ensuring inclusive access, e-commerce leaders can harness AI’s potential responsibly, fostering trust and driving growth in 2025.
AI is used in E-commerce to to improve product search and recommendations, Marketing and Advertising, Fraud Detection, Inventory Management, Logistics and many more areas.
Amazon has introduced Rufus, its latest generative AI-powered conversational shopping experience, serving as the company's new AI shopping assistant.
AI tailors shopping experiences by analyzing user preferences. Google’s AI Mode, unveiled at I/O 2025, uses a vast product database to suggest items like weather-appropriate bags. Amazon’s Rufus and Etsy’s tools similarly refine suggestions based on user behavior.
Google’s 2025 virtual try-on feature lets shoppers upload photos to see clothing on themselves, using advanced AI to model fabric fit across body types, boosting confidence in online purchases.
AI optimizes e-commerce logistics by streamlining operations. Amazon accelerates deliveries, Domino’s cuts wait times, and Google’s agentic checkout tracks prices for timely purchases, ensuring efficient supply chains.
AI must avoid biases in recommendations or pricing to maintain trust. Google’s I/O 2025 try-on tool promotes fairness by supporting diverse users, requiring ongoing audits to ensure ethical standards.
Small retailers often lack AI resources. Platforms like Google and eBay can offer cost-effective tools, such as automated listings or personalized ads, to level the playing field.