AI agents are in the process of flipping the shopping script. No longer confined to answering basic questions like chat bots, these intelligent assistants are evolving into virtual personal shoppers, inventory wizards, and customer service ninjas. While nearly 80% of companies have deployed generative AI in some shape or form, roughly the same percentage report no material impact on earnings. 

Your tech stack might be the bottleneck that prevents these AI superpowers from actually working. Learn how to prepare your eCommerce platform for the agentic AI revolution.

What Is Agentic AI in eCommerce?

Think of agentic AI as your most capable sales associate, but one that never sleeps, never forgets a customer’s preferences, and can handle thousands of conversations simultaneously. According toGoogle Cloud research, these systems operate through a continuous cycle of perception, planning, action, and reflection.

In retail, this translates to AI agents that can understand nuanced requests like “find me a dress for a beach wedding under $200,” browse your entire catalog, check real-time inventory, and guide shoppers through the complete purchase journey.Industry research shows 75% of retailers now say AI agents will be essential to remain competitive, with 43% already piloting autonomous systems.

Game-Changing Agentic AI Features for Your Tech Stack

The next wave of AI agents will revolutionize how customers discover, evaluate, and purchase products:

Virtual Personal Shoppers

These AI agents remember past purchases, understand style preferences, and suggest complete outfits based on behavioral analysis and real-time conversation context. Walmart has deployed generative agentic AI across retail workflows, including personal shopping assistants that provide item comparisons and recommendations.

Intelligent Inventory Assistants

AI agents that monitor stock levels, predict demand patterns, and automatically reorder products before you run out. Sainsbury’s uses AI agents to manage inventory across hundreds of stores, analyzing sales data, seasonal trends, and external factors like weather to optimize allocation and reduce stockouts.

Conversational Commerce

Instead of browsing categories, customers can have natural conversations about their needs. An AI agent can understand “I need something warm for my hiking trip next weekend” and factor in weather forecasts, size preferences, and past purchases to deliver personalized results.

Proactive Customer Service

These agents monitor order status, shipping delays, and product reviews to reach out proactively with solutions. Amazon leverages AI agents to reduce decision fatigue by autonomously searching, comparing, and managing shopping lists based on individual preferences.

The Technical Foundation: What Your Stack Needs

Preparing for agentic AI requires rethinking your entire technical foundation. Here’s what you need to get right:

API-First Architecture

AI agents need to interact with every part of your eCommerce ecosystem seamlessly. Your product catalog, inventory management, customer data, payment systems, and logistics platforms must all be accessible through well-documented APIs. Without this flexibility, AI agents become isolated tools rather than integrated experiences.

Real-Time Data Pipelines

Agentic AI thrives on fresh, accurate data. Your tech stack needs to provide real-time access to inventory levels, customer behavior, pricing changes, and product information. Stale data leads to disappointed customers when an AI agent promises something you can’t deliver.

Unified Customer Profiles

AI agents need a complete view of each customer across all touchpoints. This means integrating data from your website, mobile app, in-store visits, customer service interactions, and email campaigns into a single, accessible profile. Without this 360-degree view, AI agents can’t provide truly personalized experiences.

Scalable Infrastructure

AI workloads can spike unpredictably, especially during peak shopping periods. Your infrastructure needs to handle sudden increases in processing power without breaking performance or your budget. Cloud-native solutions provide the elasticity that AI agents demand.

Security and Privacy Framework

AI agents will have access to sensitive customer data and the ability to make purchases on customers’ behalf. Your security framework must protect this data while enabling seamless AI interactions. This includes robust authentication, encryption, and audit trails for all AI actions.

Making It Work: Unified and Composable Commerce and AI

The retailers best positioned for agentic AI are those already embracing composable commerce architectures, such as:

  • Rapid AI Integration: With a composable setup, you can plug in AI capabilities without rebuilding your entire platform. Want to test a new AI-powered recommendation engine? Simply connect it through APIs. Need to upgrade your customer service AI? Swap out components without affecting your core commerce operations.
  • Experimentation Without Risk: Composable architectures let you test AI features with specific customer segments or product categories before rolling them out broadly. You can A/B test different AI approaches and measure their impact on conversion rates and customer satisfaction.
  • Best-of-Breed AI Tools: Rather than being locked into one vendor’s AI capabilities, composable commerce lets you integrate specialized AI tools for different functions. You might use one AI for visual search, another for personalized recommendations, and a third for customer service – all working together seamlessly.

The flexibility of unified and composable commerce platforms means you can scale globally while maintaining the agility to adopt new AI capabilities as they emerge. This approach turns your tech stack from a limitation into a competitive advantage.

Your AI-Ready Action Plan

The agentic AI revolution is closer than you think. Start by auditing your current tech stack for API availability, data quality, and integration capabilities. Focus on building the technical foundation – real-time data access, unified customer profiles, and flexible architecture – that will enable AI agents to deliver meaningful value.

WithAI transforming retail at unprecedented speed, the brands that prepare now will have AI agents enhancing customer experiences while their competitors are still figuring out basic integrations. The future of eCommerce is conversational, intelligent, and proactive – make sure your tech stack is ready for the transformation.

Learn more about mastering AI in retail and preparing your eCommerce platform for what’s next.