Most Latin American E-Commerce Platforms Lag in AI Adoption

Most Latin American e-commerce platforms show critical gaps in performance and AI adoption, according to Google Cloud and R/GA. In Mexico, slow load times, weak search intelligence, and limited personalization constrain conversion in retail, pharmacy, and supermarket sectors, where rising competition and digitally demanding consumers make AI-driven optimization a near-term operational priority.

Eighty percent of major e-commerce platforms in Latin America demonstrate critical deficiencies in technical performance and AI adoption, reveal Google Cloud and the innovation agency R/GA in the Retail Garage 2026 study.

The integration of advanced technologies has become a requirement for sector competitiveness, say the companies. The report emphasizes that AI is fundamental to make the experience more intuitive and efficient, so that brands stand out and create more connections with their customers.

"We are seeing that many digital experiences continue to have friction at the most critical moment: when the customer is ready to buy,” says Marco Pieck, Field Marketing Manager, Google Cloud in Mexico. “The challenge for retailers is to redesign the entire experience so that technology understands intent, context, and need in real time. AI now allows us to move from rigid flows to truly intuitive experiences, where searching, buying, and receiving support are all part of the same process."

Retail in the country is going through one of the most competitive moments in its history, says Carlos Morales, Director of Corporate Retail accounts, Google Cloud. Morales notes that on the one hand, consumers expect comprehensive, fast, and personalized experiences. On the other, retailers still have opportunities to drive innovation with the power of AI and enrich the experience they provide through their e-commerce site. 

“Not enabling these types of experiences is not a technical limitation; it is a business opportunity that is being missed," says Morales.

Retail Garage 2026 Study Findings

The research analyzed 16 million data points to diagnose the digital experience of 30 leading retailers in the region. It evaluated 30 organizations within the departmental, pharmacy, and supermarket subindustries. Seventeen of those companies operate in Mexico.

Experts in technology, strategy, and user experience (UX) from R/GA performed the research. They simulated authentic consumer journeys from June 30 to Aug. 8, 2025. The team also used Lighthouse, which is an open-source tool from Google, to audit public metrics such as page load times, technical errors, and accessibility.

Technical analysis using Lighthouse indicates that most analyzed retailers do not meet performance standards. Twenty-four of the 30 e-commerce sites failed to load principal content within the ideal time of 2.5 seconds. The general average for Largest Contentful Paint (LCP) was 4.94 seconds. Specifically, supermarkets reached an average of 5.49 seconds, and departmental stores reached 4.58 seconds. Eighty percent of platforms negatively impacted users by blocking actions during content loading. Furthermore, 21 of the 30 sites recorded unexpected layout shifts that cause disorientation.

The initial purchase stage shows significant friction related to interpreting user intent. Sixteen of the 30 e-commerce sites displayed no results for search queries with typographical errors. This failure occurs despite the fact that one out of every 10 searches on Google contains a typo. Only nine platforms provided relevant results for semantic searches. Additionally, no retailer presented multimodal search, which combines image and text. Only two offered voice search. In Mexico, seven of the 17 e-commerce sites showed no results for typos, and 10 of the 17 failed to provide relevant semantic results.

Personalization remains underutilized throughout the middle of the funnel. Only five retailers offered search results based on a customer profile, and only nine made recommendations based on browsing history. Twelve of the 30 e-commerce sites did not offer complementary products on the product page. This represents a significant gap because effective cross-selling strategies can increase sales by up to 20%. Regarding customer reviews, only three of the 12 sites that allowed reviews used AI to generate automated summaries.

Convenience determines final conversion in the last stage of the journey. Only 10 retailers offered standard delivery, scheduled delivery, and in-store pickup simultaneously. Just five platforms displayed real-time inventory availability on search result pages. Virtual assistant quality is largely rudimentary. Among the 25 retailers with a chatbot, only eight understood natural language. Only three chatbots transferred a service to a human agent successfully without losing conversation context. Finally, only 11 of the 25 assistants used sentiment analysis.

Data for the 17 Mexican retailers reflects regional challenges. Fourteen of the 17 failed to meet the ideal LCP time. Eleven of the 17 continue to impact users with unexpected design shifts. Only three of the 17 retailers reached the ideal accessibility score of 90 points or more. Furthermore, only two chatbots in Mexico demonstrated the ability to act as purchase assistants.

Future Outlook

Organizations are expected to move toward natively multimodal AI models to manage structured and unstructured data. To support this transition, Google Cloud provides solutions such as Vertex AI and the Gemini model. These tools allow businesses to modernize catalogs, optimize delivery routes with Cloud Fleet Routing (CFR), and improve developer productivity through AI-assisted code generation. 

The report argues that AI adoption is necessary to automate repetitive tasks in the back office, optimize marketing investments, and improve productivity in physical stores.