The way consumers shop online is undergoing a fundamental shift. A stunning 60% of shoppers already use AI in their shopping journey (mirakl.com). Instead of scrolling through endless listings, people are beginning to rely on agentic shopping, delegating research, comparison, and even purchases to AI systems acting as personal shopping agents. This evolution means eCommerce brands must now consider not just human shoppers, but also AI-driven assistants that filter and choose products on users’ behalf. Generative Engine Optimization (GEO) has emerged as the strategic response to this change, ensuring brands remain visible and competitive in the era of AI-powered commerce.
Agentic Commerce: AI as the New Shopper
We’re entering a world where AI platforms play the role of the savvy consumer, and eCommerce’s playbook is changing. Major tech companies are already embracing agentic commerce. For example, Amazon’s Rufus AI assistant now helps customers find products, compare features, and answer shopping questions right inside Amazon’s app (aboutamazon.com). Amazon reports that shoppers who use Rufus are 60% more likely to complete a purchase than those who don’t (timesofindia.indiatimes.com), a massive boost in conversion. Likewise, Google is integrating its Gemini AI model into Search to handle complex shopping tasks. In Google’s new AI shopping mode, you can get a personalized overview of products and even ask an agentic checkout to buy an item on your behalf when the price meets your criteriav (blog.google). OpenAI’s introduction of a GPT Store for custom ChatGPT assistants underscores this trend as well: specialized shopping GPTs can now serve as virtual product experts and deal-finders (ecomtent.ai). These shifts illustrate why brands need to optimize for AI visibility; the new gatekeepers of online shopping are algorithms and AI agents, not just human consumers.
Three Layers of AI Commerce Readiness: Readability, Reputation, Recurrence
To thrive in this agent-led commerce era, oakpool emphasizes a framework called the “Three Layers of AI Commerce Readiness.” It consists of Readability, Reputation, and Recurrence, three strategic layers to ensure your brand is agent-ready:
- Readability: This is about making your product data and content machine-friendly. AI agents can’t recommend what they can’t interpret. Brands must provide rich, structured information (titles, descriptions, attributes, schema markup) so AI systems can easily crawl and understand it (mirakl.com). Think of technical clarity and context: product listings should answer real user questions in natural language, include specs and usage details, and be formatted for easy parsing. In short, ensure an AI can “read” everything about your product with no ambiguity.
- Reputation: AI shopping agents heavily favor products and brands they perceive as trustworthy and well-liked. In practice, this means cultivating strong customer reviews, ratings, and credible content. Positive reviews and high ratings don’t just influence human shoppers, they directly feed AI models’ rankings and recommendations (mirakl.com). Generative AI systems are trained to prioritize brands with excellent reputations and authoritative data, drawing on principles similar to E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) (flatlineagency.com). To boost this layer, brands should encourage authentic reviews, highlight endorsements or awards, and ensure all information (pricing, availability, compliance) is accurate. Your brand’s digital footprint must signal reliability at every turn.
- Recurrence: This layer is about consistent presence and continuous optimization. AI agents learn over time; the more consistently your brand appears with relevant, updated information, the more likely the AI will include you in recommendations. Brands need to keep product content fresh and aligned with current trends or seasonal needs (syndigo.com). For example, updating descriptions and FAQs quarterly to reflect new use cases or consumer questions can keep you in the AI’s consideration set (syndigo.com). Recurrence also means maintaining omnichannel consistency; your product data and messaging should be uniform across your website, marketplaces, and any data feeds. If an AI agent sees the same trustworthy, up-to-date information about your product everywhere, it will “learn” to reliably present your brand to users again and again.
Optimizing Products for AI Shopping Agents
The rise of agentic shopping demands that brands optimize their product data, metadata, and digital visibility with AI agents in mind. In practice, this means enriching every product listing with comprehensive attributes, contextual details, and structured metadata so that an AI agent can find exactly what it needs. Clean, well-structured content is non-negotiable when an AI is deciding which product to recommend. For instance, including detailed specs, sizing info, ingredient lists, and usage instructions (all marked up with schema) makes it far more likely an AI like ChatGPT or Google’s SGE will surface your item as a top answer (mirakl.com). Social proof is another key factor: AI models analyze reviews and ratings, so a product with a higher average rating and thorough reviews may be chosen over a slightly cheaper alternative (mirakl.com). Brands should actively monitor and respond to reviews to improve this trust signal. Many forward-thinking companies are now leveraging specialized tools to meet these new requirements, like our free oakpool.ai tool. These give businesses a way to audit and enhance their listings for AI visibility. By using such solutions to refine content and prioritize data quality, eCommerce brands can ensure they appear prominently when an AI agent is shopping.
The age of agentic commerce is already here. To remain competitive, brands must combine classic eCommerce savvy with a new discipline of Generative Engine Optimization. By focusing on the readability of their data, building an impeccable reputation through content and reviews, and maintaining recurrence through consistent updates, businesses can become the go-to choices for AI-driven shoppers. In this new landscape, those who proactively optimize for AI will earn the trust (and clicks) of the algorithms that increasingly shape consumer decisions.
oakpool.ai is the software and services sister company of oakpool. We design and build infrastructure, intelligence, automation, and services that enable brands to show up powerfully in the AI Search era. Our free GEO (AI Search Optimization) tool is the first of its kind and the only free solution on the market.
