Automated assistants are beginning to handle tasks that previously took consumers through search engines, retailer websites and sponsored listings. Their development poses a new challenge to the advertising models of major retail platforms and to brands competing for attention.
The arrival of artificial intelligence systems capable of researching, comparing and purchasing products on a consumer’s behalf could change the economics of digital retail advertising.
The development is important because online shopping is not simply a transaction. For retailers and technology platforms, the journey from search to purchase creates opportunities to sell advertising, promote products and gather information about customer preferences.
A shopping agent changes that sequence. Instead of reviewing pages of search results and promotional offers, a consumer may ask an automated assistant to find a suitable product within a specified budget, compare options and complete the purchase.
The technology remains at an early stage, and the extent to which customers will delegate purchases to AI is uncertain. Nevertheless, the possibility is attracting attention from retailers whose advertising businesses have become important sources of revenue.
Recent Reuters reporting on agentic shopping has examined the potential consequences for businesses such as Amazon and Walmart, whose advertising services benefit from direct engagement with shoppers.
Advertising depends on the customer’s journey
Retail media has expanded as major online marketplaces sell prominent positions in search results, product pages and other digital properties.
Brands pay for these placements because customers browsing a retailer’s website are often close to making a purchase.
The commercial value of the advertisement depends partly on visibility. A sponsored item placed near relevant search results may influence which products a shopper considers.
An AI shopping agent could alter this arrangement by filtering a large catalogue before the consumer sees individual products.
If an assistant returns three recommendations rather than hundreds of search results, the question becomes how those recommendations are selected and whether commercial promotions influence them.
The answer is not yet settled. Different agents may use different data sources, ranking methods and commercial arrangements.
Some may direct users to retailer websites. Others could complete more of the transaction within the assistant’s interface.
For brands, the difference could be substantial: spending to secure a prominent position on a retailer’s website may have less effect if customers never visit that page.
What happens to retail media revenues?
Retailers have a financial incentive to preserve valuable advertising opportunities as shopping interfaces evolve.
They may introduce sponsored recommendations inside AI experiences, provide structured product information to external agents or develop their own assistants to retain customer relationships.
However, sponsored recommendations create questions about transparency and trust.
A shopper asking an assistant for the best available product may assume that its response reflects price, suitability and other requested criteria. Commercial influence should be clearly distinguished from independent comparison.
For advertisers, the measurement challenge is equally important. Conventional campaign metrics such as impressions and clicks become less useful when an AI system makes several selections on behalf of a customer without displaying each intermediate option.
Marketing teams may need to pay closer attention to inclusion in product recommendations, the accuracy of product data, conversion rates and the cost of reaching customers through new interfaces.
It would be premature to conclude that retail advertising will disappear. The more plausible development is a change in where advertisements appear, how they are labelled and how their effectiveness is measured.
Product information becomes a competitive asset
If AI agents rely on structured product data, retailers and manufacturers will need to ensure that descriptions, specifications, prices and availability are accurate.
Poor data can cause an otherwise relevant product to be excluded from a recommendation or presented incorrectly.
The problem is particularly acute for products whose suitability depends on technical characteristics, compatibility, delivery conditions or regulatory certification.
Brands should therefore review how product information is distributed across their own websites, marketplaces, merchant feeds and other commercial channels.
Claims should be consistent and supported by evidence. A product described differently across multiple sources may create difficulties for automated comparison.
Reliable information does not guarantee a high position in an AI system’s recommendations, and no universal method exists for influencing all shopping agents. It does, however, make the product easier to assess accurately.
New questions for competition and consumer protection
Automated product selection could raise concerns familiar from earlier debates about search engines and digital marketplaces.
Who determines the ranking criteria? Can participating retailers obtain preferential treatment? Are shoppers told when recommendations are sponsored? Can smaller businesses compete for inclusion?
European legislation already addresses aspects of online consumer protection, misleading commercial practices and platform conduct.
The Digital Services Act, the Digital Markets Act and existing consumer protection rules may become relevant depending on the specific business model and services involved.
However, the application of those rules should not be assumed to be identical for every AI assistant. Regulatory obligations depend on matters including the provider’s role, the nature of the service and the commercial practices used.
Competition authorities may also examine whether access to product catalogues, payment systems or customer data gives large platforms an advantage.
What communications teams should prepare
Marketing and communications departments do not need to abandon existing search, marketplace or retail media strategies. Consumer adoption, platform design and the commercial economics of AI agents remain unsettled.
They should nevertheless develop ways of monitoring whether automated assistants present their products accurately, which competing products appear alongside them and how purchasing recommendations differ across services.
Companies also need to identify who is responsible for updating technical specifications, correcting misleading descriptions and responding when a platform or agent provides inaccurate information.
For corporate communications teams, this is a question of reputation as well as sales. An automated assistant can reproduce incorrect claims about a product or business without the brand directly controlling the interaction.
The changing shopping interface could therefore make verified, consistent product information more important.
For retailers, the challenge is preserving valuable commercial relationships when the consumer’s first interaction may take place elsewhere.
For brands, it is ensuring that products remain discoverable and accurately represented even when an algorithm, rather than a person browsing a website, makes the initial selection.
