It is expecting a 3,200% increase in traffic from generative AI sources compared to last year. Consumers are increasingly leveraging AI assistants like ChatGPT, Perplexity, and Amazon’s Rufus to find products, compare prices, and snag the best deals across various retailers. Adobe’s analysis further reveals that these AI-driven visitors are significantly more engaged on retail sites.
Let’s have a look the impact on Amazon’s Infrastructure:
- Scaling compute and storage: Amazon has historically prepared for Prime Day by significantly scaling its cloud infrastructure. For example, in 2022, Amazon increased Amazon EC2 compute instances by 12% and added 152 petabytes of storage to handle peak loads, processing trillions of requests and hundreds of billions of transactions daily. For 2025, with generative AI traffic expected to surge by 3,200% year-over-year, Amazon will have to further expand its AI-optimized compute resources, including GPU-powered instances and AI chips, to serve millions of real-time inference requests while maintaining low latency.
- Advanced AI infrastructure: Amazon’s AI shopping assistant Rufus and other AI features rely on large language models (LLMs) that require highly efficient, scalable deployment to meet strict latency SLAs (e.g., 300 ms response times) during peak traffic. Amazon uses innovations like parallel decoding and specialized AI chips to improve inference speed and power efficiency, critical for managing the massive AI workload surges on Prime Day.
- Automatic scaling and resilience: Services like Amazon Aurora automatically scale with traffic increases to keep checkout and other critical processes smooth and responsive. The infrastructure must handle not only raw traffic but also the complexity of AI-driven personalization and dynamic content generation without outages.
What about the Impact on Customer Experience?
- Personalized shopping at scale: AI-powered tools such as Rufus, AI-generated shopping guides, and interest-based recommendations aim to solve the long-standing challenge of deal discovery among millions of items. These AI assistants curate product selections, reducing choice overload and helping shoppers find relevant deals quickly.
- Enhanced engagement and conversion: Adobe’s analysis shows AI-driven visitors stay 8% longer, view 12% more pages, and bounce 23% less than non-AI referrals, indicating deeper engagement and better-informed purchasing decisions. AI helps shoppers with product research, deal spotting, gift ideas, and personalized recommendations, improving satisfaction and increasing average order value.
- Mobile and AI synergy: Mobile commerce accounts for over half of Prime Day sales, and AI-powered mobile shopping assistants are increasingly active, spotting real-time deal drops and enabling seamless, on-the-go purchasing. This integration of AI and mobile enhances convenience and responsiveness.
- Sustainability and cost efficiency: AI optimizations also help reduce power consumption and operational costs, contributing to more sustainable infrastructure management during the intense Prime Day event.
Amazon’s infrastructure and AI innovations are critical to delivering a seamless, personalized, and high-performance shopping experience during the largest and longest Prime Day ever, despite the unprecedented surge in generative AI traffic.