From Browsing to Buying: How AI Agents Enhance Online Shopping

Editor’s note: This post is part of the AI On blog series, which explores the latest techniques and real-world applications of agentic AI, chatbots and copilots. The series also highlights the NVIDIA software and hardware powering advanced AI agents, which form the foundation of AI query engines that gather insights and perform tasks to transform everyday experiences and reshape industries.

Online shopping puts a world of choices at people’s fingertips, making it convenient for them to purchase and receive orders — all from the comfort of their homes.

But too many choices can turn experiences from exciting to exhausting, leaving shoppers struggling to cut through the noise and find exactly what they need.

By tapping into AI agents, retailers can deepen their customer engagement, enhance their offerings and maintain a competitive edge in a rapidly shifting digital marketplace.

Every digital interaction results in new data being captured. This valuable customer data can be used to fuel generative AI and agentic AI tools that provide personalized recommendations and boost online sales. According to NVIDIA’s latest State of AI in Retail and Consumer-Packaged Goods report, 64% of respondents investing in AI for digital retail are prioritizing hyper-personalized recommendations.

Smart, Seamless and Personalized: The Future of Customer Experience

AI agents offer a range of benefits that significantly improve the retail customer experience, including:

• Personalized Experiences: Using customer insights and product information, these digital assistants can deliver the expertise of a company’s best sales associate, stylist or designer — providing tailored product recommendations, enhancing decision-making, and boosting conversion rates and customer satisfaction.
• Product Knowledge: AI agents enrich product catalogs with explanatory titles, enhanced descriptions and detailed attributes like size, warranty, sustainability and lifestyle uses. This makes products more discoverable and recommendations more personalized and informative, which increases consumer confidence.
• Omnichannel Support: AI provides seamless integration of online and offline experiences, facilitating smooth transitions between digital and physical retail environments.
• Virtual Try-On Capabilities: Customers can easily visualize products on themselves or in their homes in real time, helping improve product expectations and potentially lowering return rates.
• 24/7 Availability: AI agents offer around-the-clock customer support across time zones and languages.

Real-World Applications of AI Agents in Retail

AI is redefining digital commerce, empowering retailers to deliver richer, more intuitive shopping experiences. From enhancing product catalogs with accurate, high-quality data to improving search relevance and offering personalized shopping assistance, AI agents are transforming how customers discover, engage with and purchase products online.

AI agents for catalog enrichment automatically enhance product information with consumer-focused attributes. These attributes can range from basic details like size, color and material to technical details such as warranty information and compatibility.

They also include contextual attributes, like sustainability, and lifestyle attributes, such as “for hiking.” AI agents can also integrate service attributes — including delivery times and return policies — making items more discoverable and relevant to customers while addressing common concerns to improve purchase results.

Amazon faced the challenge of ensuring complete and accurate product information for shoppers while reducing the effort and time required for sellers to create product listings. To address this, the company implemented generative AI using the NVIDIA TensorRT-LLM library. This technology allows sellers to input a product description or URL, and the system automatically generates a complete, enriched listing. The work helps sellers reach more customers and expand their businesses effectively while making the catalog more responsive and energy efficient.

AI agents for search tap into enriched data to deliver more accurate and contextually relevant search results. By employing semantic understanding and personalization, these agents better match customer queries with the right products, making the overall search experience faster and more intuitive.

Amazon Music has optimized its search capabilities using the Amazon SageMaker platform with NVIDIA Triton Inference Server and the NVIDIA TensorRT software development kit. This includes implementing vector search and transformer-based spell-correction models.

As a result, when users search for music — even with typos or vague terms — they can quickly find what they’re looking for. These optimizations, which make the search bar more effective and user friendly, have led to faster search times and 73% lower costs for Amazon Music.

AI agents for shopping assistants build on the enriched catalog and improved search functionality. They offer personalized recommendations and answer queries in a detailed, relevant, conversational manner, guiding shoppers through their buying journeys with a comprehensive understanding of products and user intent.

SoftServe, a leading IT advisor, has launched the SoftServe Gen AI Shopping Assistant, developed using the NVIDIA AI Blueprint for retail shopping assistants. SoftServe’s shopping assistant offers seamless and engaging shopping experiences by helping customers discover products and access detailed product information quickly and efficiently. One of its standout features is the virtual try-on capability, which allows customers to visualize how clothing and accessories look on them in real time.

Defining the Essential Traits of a Powerful AI Shopping Agent

Highly skilled AI shopping assistants are designed to be multimodal, understanding text- and image-based prompts, voice and more through large language models (LLMs) and vision language models. These AI agents can search for multiple items simultaneously, complete complicated tasks — such as creating a travel wardrobe — and answer contextual questions, like whether a product is waterproof or requires drycleaning.

This high level of sophistication offers experiences akin to engaging with a company’s best sales associate, delivering information to customers in a natural, intuitive way.

The building blocks of a powerful retail shopping agent include:

• Multimodal and Multi-Query Capabilities: These agents can process and respond to queries that combine text and images, making search processes more versatile and user friendly. They can also easily be extended to support other modalities such as voice.
• Integration With LLMs: Advanced LLMs, such as the NVIDIA Llama Nemotron family, bring reasoning capabilities to AI shopping assistants, enabling them to engage in natural, humanlike interactions. NVIDIA NIM microservices provide industry-standard application programming interfaces for simple integration into AI applications, development frameworks and workflows.
• Management of Structured and Unstructured Data: NVIDIA NeMo Retriever microservices provide the ability to ingest, embed and understand retailers’ suites of relevant data sources, such as customer preferences and purchases, product catalog text and image data, and more, helping ensure AI agent responses are relevant, accurate and context-aware.
• Guardrails for Brand Safe, On-Topic Conversations: NVIDIA NeMo Guardrails are implemented to help ensure that conversations with the shopping assistant remain safe and on topic, ultimately protecting brand values and bolstering customer trust.
• State-of-the-Art Simulation Tools: The NVIDIA Omniverse platform and partner simulation technologies can help visualize products in physically accurate spaces. For example, customers looking to buy a couch could preview how the furniture would look in their own living room.

By using these key technologies, retailers can design AI shopping agents that exceed customer expectations, driving higher satisfaction and improved operational efficiency.

Retail organizations that harness AI agents are poised to experience evolving capabilities, such as enhanced predictive analytics for further personalized recommendations.

And integrating AI with augmented- and virtual-reality technologies is expected to create even more immersive and engaging shopping environments — delivering a future where shopping experiences are more immersive, convenient and customer-focused than ever.

Learn more about the AI Blueprint for retail shopping assistants.