Artificial intelligence is ceasing to be merely an automation tool and is assuming a potentially more structural role in the transformation of retail. In an analysis of the possible futures of agentic AI in the sector, EY identifies four scenarios (Constraint, Growth, Transform, and Collapse) that reflect different paces and degrees of technological adoption. In the most transformative scenario, AI is not limited to improving processes: it alters the very way the retailer creates value, manages customer relationships, and distributes profits across the various business activities.

According to data from the “EY CEO Outlook Survey” cited in the analysis, 70% of retail leaders believe that profitable growth will be increasingly driven by non- core activities . These areas include retail media , subscriptions, services, and marketplaces – businesses that may gain relative importance compared to the traditional margin on product sales.

The trend is already visible in many operators, who are seeking to monetize assets such as data, audience, logistics, media , financial services, and technology. This evolution suggests that the retailer of the future may generate an increasing share of profit not only from what they sell, but also from the capabilities they build around customer relationships.

Stores can become omnichannel infrastructures.

The transformation should also reach physical networks. According to EY, 84% of industry leaders expect to transform their store networks to better support omnichannel models. This means that the store ceases to function solely as a point of sale and begins to assume multiple functions, namely collection and return points, micro-logistics centers, experience spaces, service channels, and infrastructure for digital commerce. In this model, the economic value of a store is not measured solely by sales made in the physical space.

More than half of the leaders surveyed, 52%, also believe that competitive dynamics are changing and that competition from companies outside traditional retail is increasing. Technology platforms, logistics operators, fintechs , marketplaces , and media companies can compete for activities that were previously more clearly integrated into the retailer's business. Agent AI can accelerate this change by allowing different systems to search, compare, recommend, and perform tasks on behalf of the consumer.

Retailers can transition from sellers to ecosystem managers.

In a scenario of profound transformation, EY acknowledges that large operators may cease to be merely product distributors and begin to function as orchestrators of ecosystems. Capabilities currently considered support functions may transform into new sources of B2B revenue. Logistics, data, advertising, technology, and financial services may become marketable businesses for third parties, while some functions may be outsourced to specialized partners. The result could be a model in which a significant portion of the profit comes from areas that today would not even be classified as traditional retail.

Retail media is one of the clearest examples of this shift. Retailers possess transactional data, knowledge about purchasing behavior, and direct contact with consumers—assets that can be monetized through advertising and media services. With AI, these capabilities can become even more precise, enabling real-time campaign segmentation, personalization, and automation. In this scenario, selling advertising space, data, or access to audiences can become as strategic as managing categories and product assortment.

Technological platforms can concentrate power.

EY also paints a less favorable picture for retailers. In the so-called Collapse scenario, a small number of technology platforms could concentrate the most advanced AI models and charge a high price for access.

Large retailers would have a greater capacity to absorb these costs, while medium-sized operators could become more dependent on platforms or become targets for consolidation.

The consultancy notes that the five largest global retailers already account for approximately 66% of the market capitalization of the 20 largest operators analyzed.

If AI agents begin to mediate discovery, comparison, and purchase, retailers may lose some direct contact with the consumer, a change with significant implications. Today, much of a retailer's value stems from accumulated knowledge about purchasing habits, frequency, preferences, and response to promotions. If the decision becomes filtered by external systems, the competition for the customer could also become a competition for control of the interface and data.

Human service can gain value precisely because of AI.

Paradoxically, the greater the presence of automation, the greater the potential commercial value of human interaction. EY believes that smaller or specialized operators can differentiate themselves through authenticity, specialized knowledge, local relevance, experience, and human service.

In categories where advice, trust, or experience carry significant weight, human contact can become a differentiating factor that is difficult for automated systems to replicate. Technology does not necessarily eliminate the value of people; it can enhance the value of moments when human interaction is truly relevant.

Nevertheless, companies' preparedness for this change still has gaps. According to the analysis, 91% of ICT professionals working in retail believe that organizations need to better understand how to combine different transformative technologies to create value. Furthermore, 83% consider it necessary to deepen their knowledge of the risks associated with artificial intelligence.

In other words, the challenge lies not only in adopting new tools, but in integrating them coherently with existing systems, processes, and business models.

Trust remains a barrier.

The adoption of AI will also depend on consumer trust. EY reports that 59% of consumers are concerned that organizations will not take responsibility for the negative consequences of using AI. Only 47% say they trust that companies will adequately protect the data used by their systems.

For retailers, governance , data protection, and transparency can become competitive factors as relevant as price and convenience.

Regardless of which scenario prevails, EY identifies three major areas of preparedness. The first is to strengthen technological infrastructure and interoperability, so that systems can incorporate new tools without requiring deep rebuilds. The second involves integrating governance , cyber-resilience, and trust from the outset. The third is to preserve human differentiation by investing in talent, culture, service, and experience.

The conclusion of the analysis is that there will likely not be a single future for retail. Different categories, geographies, and formats may adopt agentic AI at very different rates.