Mars Snacking is testing how its brands appear in AI-generated shopping recommendations while reorganizing teams around a more connected approach to commerce. The new details offer an unusually practical view of what preparing for agentic shopping looks like inside a large consumer-goods business.
Neil Reynolds, Mars's global chief customer officer, described exploratory partnerships with emerging technology companies to understand how products surface in large language models and which information sources influence those results. The work is still about establishing a baseline, not announcing that AI assistants are already buying groceries for Mars customers.
The effort builds on Mars's October research into the future of shopping, developed with Kantar and Synthesis. That earlier work forecast two parallel developments: more routine purchases handled automatically, and physical stores becoming more experiential. The more recent disclosure is about the organizational and measurement steps Mars is taking in response.
Consumer brands have long competed for search visibility, retail listings and prominent positions in-store. AI shopping assistants introduce another layer between a shopper's request and the products that receive consideration. Mars is starting by asking what evidence explains whether its brands appear in those answers.
Reynolds framed a central question as “how do we make sure our brands are discoverable by the LLMs”. His answer was not a finished optimization system. The company is working with emerging technology partners to learn how its products currently show up, and where that information comes from.
An AI shopping assistant may not have an aisle, but it still shapes which products enter consideration.
For marketers, the distinction between being mentioned and being purchased matters. A brand could become visible to an assistant without winning a transaction. Mars is therefore treating discoverability and conversion as connected but separate problems, rather than assuming improved AI visibility automatically leads to growth.
That reasoning also makes source quality more consequential. Product descriptions, retailer catalogues, availability information and other underlying records can influence how a brand is represented, although the interview does not disclose which sources Mars has found to be most influential. Claims about an AI-visibility improvement would require measured evidence that the company has not yet published.
Mars is also changing who works on the problem. Reynolds described forming One Demand performance squads that bring together brand management, consumer insights, key accounts, category teams and agency partners. The structure is designed to connect the people responsible for consumer demand with those closer to retail execution.
That is a more substantial organizational response than assigning AI search to an SEO specialist. The brand team may understand positioning, the account team may understand retailer requirements, and the data team may identify gaps in product information. An answer generated outside any one of those teams still depends on decisions made across all of them.
The deeper constraint may be coordination rather than a lack of new tools.
Part of the infrastructure predates this interview. In June 2025, Mars appointed Publicis to lead connected commerce and several other marketing functions. Reynolds now describes the partnership as a route to linking media, commerce…
