Retailers are increasingly turning to Generative AI as a new channel for customers to discover, interact with, and purchase their products. Walmart stores in the US have integrated shopping features within ChatGPT, allowing customers to browse products and utilize the ‘Instant Checkout’ option. Having LLMs surface content of service providers is highly likely to be the next ‘in’ thing in retail and e-commerce in 2026. According to futurist Bernard Marr, in a ‘zero-click’ world, they could ask AI Assistants to search and purchase the right product within their budget.
Call it GEO (Generative Engine Optimization); according to The Wall Street Journal, CMO Today blog, agentic commerce has strategic implications for retail brands as retail websites witnessed a 4,700% surge in traffic via AI-assistants between July 2025 and July 2024. AI agents (agentic commerce) are likely to assist consumers in comparing products and prices, applying rewards, and tracking product deliveries.
While agentic commerce (see point 1 below) is just one part, the following section provides a quick recap of what’s trending for 2026 and beyond (references are listed toward the end).
Summary of what’s trending:
- Agentic Commerce Optimization
- AI-led dynamic pricing
- AI-led co-creation with shoppers
- Multi-agent ecosystems
- Voice shopping
- Gen Z’s consciousness
- AI-led merchandizing
- Live-streamed experiences
AI agents are driving retail transformation as engagement shifts from SEO to Agentic Commerce Optimization (ACO). Innovators should focus on ROI, adoption, modernization, data governance, payments, brand-owned agents, and AI regulation.
Agents can deliver personalized offers, engage persistently across channels, target non-website users, manage loyalty, monitor prices, write product info, handle inquiries, and offer sponsorship opportunities for agent interactions.
AI-led dynamic pricing is gaining traction as a few companies adopt this approach to navigate fluctuations in supply and demand. However, ethics, transparency of AI, and regulations are likely to cast a sharp eye on such practices in the months ahead. In the US, Amazon has deployed this approach to offering competitive prices to its customers. Market adaptability, personalized pricing, smarter inventory management, and revenue growth are made possible by dynamic offers.
AI in eCommerce will likely contribute toward overall supply chain efficiencies: smart demand forecasting, optimized inventory, curbing logistics costs, and improving revenues.
AI-led co-creation with shoppers is looking to take the limelight as retails can use behavioral data with GenAI to engage shoppers in the products’ creative aspects so that product concepts resonate with the current market preferences and trends based on social media analysis, sentiment mining in real-time and funneling these inputs into the product development cycle; retailers can remove the guesswork during product launches, curtail development cycles and costs, and improve the ‘market-product fit’.
Gen Z are conscious about their ethical and sustainable consumption and consider the resale value before purchasing products; circular retail models and recommerce shift into mainstream in 2026 as ‘sustainable options’ can be a differentiator when it comes to renting, refurbished products, repair and resale value.
Imagine a multi-agent AI retail ecosystem: agents coordinate on forecasting, inventory, real-time pricing, and customer service. AI conversational agents enable post-purchase support and suggest eco-friendly options to shoppers.
When stores become experience zones: AI-led merchandising is on the cards as static stores come to life with AI-infused insights. Stores become digital/immersive spaces as they morph based on shopping patterns, user behavior, time, peak foot-falls, and seasonal fluctuations. Think of autonomous product reordering, floor layout changes, and timely offers based on engagement levels.
As stores strive to become key data collection zones equipped with multiple sensors, computer vision applications, and connected devices that funnel shoppers’ behavioral inputs into AI systems for proactive and personalized services.
Voice shopping: Searching for specific jewelry by uploading a photo and visualizing how it looks is already in vogue. However, voice search will add more convenience to shoppers as they also upload product images instead of typing them. E-commerce platforms will utilize voice capabilities/commands across devices, as well as hands-free browsing and shopping. AI-led visual/voice search will yield accurate results when browsing by gender, categories, prices, features, and other criteria.
Retail and eCommerce leaders need to prepare to embrace the future. Ensure teams’ AI literacy, focus on data privacy/ethics, invest in robust/scalable infrastructure (for modular solutions) to evolve with shifting AI dynamics and customer preferences.
Retailers will strive to blend the ‘Phygital’ experience across app seamlessly in-store, and AR, as stores become ‘brand-zones’ for converging experiences and services, rather than being known solely as inventory hubs.
Commerce + entertainment: Call it ‘shoppertainment’ as shoppers have the need to be entertained. Live shopping and live-streamed shopping experiences are evolving with platforms such as TikTok Shop, ‘Instagram Live’ bring ‘check-out’ with entertainment; according to an article in Forbes magazine, China is far ahead when it comes to live commerce market and retailers need to invest in real-time engagement, on-cam storytelling and checkout flows. Research indicates that revenue from the TikTok Shop (integrated in-app shopping) is hitting record numbers.
Increasingly predictive AI applications, robotic inventory, cashierless stores, and circularity standout; retail/eCommerce leaders need to embrace the shifting tides with strong foundations in AI governance, brand trustworthiness, compliance, and the need to design experiences for agents and humans.
References