Artificial Intelligence (AI) is no longer just a search tool. It’s evolving into a full-scale commercial ecosystem. Conversational queries have now expanded into an environment where consumers can discover, evaluate and purchase items without ever accessing a traditional ecommerce site.
Google's Gemini Enterprise for Customer Experience is already piloting shopping agents that integrate directly into retailers’ ecommerce platforms, allowing shoppers to move seamlessly from product discovery to checkout within a single conversational thread. Meanwhile, Amazon is advancing agentic commerce through Rufus and “Buy for Me” - intelligent shopping assistants capable of interpreting customer goals, curating recommendations, adding items to the basket, and even placing repeat orders autonomously.
For brands, this signals the beginning of a new model where algorithms and autonomous agents decide which products get surfaced, how they are positioned and ultimately, which consumers may never even see.
Meet the AI-native consumer
AI is already woven into the daily habits of millions. People are turning to conversational tools to research products, streamline tasks and gather information in more intuitive ways. Instead of scrolling through endless product pages, consumers now simply ask, ‘What are the best noise-cancelling headphones under £100?’
The entire journey, from need to checkout, unfolds within a single conversation, reducing reliance on traditional product pages. The boundaries between search, social discovery and ecommerce continue to blur as these interactions take place across unified, AI-driven interfaces.
This year, many consumers will go a step further by delegating decision-making entirely to autonomous agents. These AI systems will evaluate specifications, compare prices across retailers, interpret reviews, assess delivery speed and complete purchases automatically based on a shopper’s predefined preferences.
Visibility in the age of algorithmic discovery
As AI becomes the first stop for product discovery, browsing behaviour is undergoing a shift. Rather than scrolling through traditional search results, people are increasingly relying on LLMs to deliver direct, summarised answers that bypass familiar listings altogether. Our latest report on AI-powered commerce shows that 87% of organisations believe that AI-powered search will positively impact their company's sales in the next 12 months, a clear signal of how critical algorithmic visibility has become.
To earn a place within these AI-generated recommendations, brands must ensure their product information is clear, structured and machine-ready. Fact-led content such as product comparisons, compatibility guidance FAQs and specialist expertise plays an essential role in strengthening topical authority. These elements help AI models recognise a brand as relevant and reliable, increasing the likelihood of being surfaced during high-intent queries.
Frameworks such as a GEO Scorecard offer a measurable way to optimise this process. By assessing a brand’s reach, ranking and sentiment across AI ecosystems, the scorecard provides a clear view of whether a brand is being recognised and elevated by AI systems – or quietly overlooked.
Preparing for autonomous agents
Unlike generative AI, which simply responds to prompts, agents operate independently and can evaluate product options, analyse sentiment and make transactional decisions at speed and scale.
Our research shows that 57% of businesses are already exploring use cases for AI agents, and 33% are already preparing for agentic commerce rollout. Some sectors are moving faster than others, with fashion emerging as a clear frontrunner. 46% of fashion businesses report they are ready for AI agents to become the primary source of customer discovery and purchase, and 44% are investigating specific agent-driven applications.
To become agent-ready, brands should begin by auditing product data to ensure accuracy, consistency and completeness across every touchpoint. Pricing, attributes, specifications and imagery must align across all channels so that AI systems receive a clear and unified view of each product. Brands should also reinforce trust signals by cultivating verified reviews, producing expertise‑driven content and securing authoritative backlinks that demonstrate credibility. Finally, using structured data formats that are easy for AI systems to interpret and ingest will help ensure that product information is not only visible but optimally usable.
Brands must also articulate their identity with clarity. Agents need to understand what you sell, as well as what you stand for. Clear, value‑led messaging, transparent policies and credible proof points help establish this context. When agents make decisions on behalf of consumers, these signals ensure a brand is recognised as relevant, reliable and meaningfully differentiated.
Machines are now influencing, if not making the decisions
As AI becomes increasingly confident in evaluating quality, reliability and value, brands must prepare to be algorithm‑ready. Structured data, verified trust signals, and factual, machine‑readable content will determine which products are recommended, and which quietly disappear.
Brands that move early will benefit from increased visibility in AI‑driven discovery and agent‑mediated purchasing. Those who hesitate risk being filtered out of the next era of buying entirely.
