GenAI as a Competitive Edge: The Autonomous Customer Journey

Retailers across Latin America are adopting generative AI to unify fragmented sales funnels and deploy autonomous agents. The shift prioritizes operational efficiency, data interoperability and workforce reskilling, as companies position to capture a projected US$4.4 trillion in value by 2029.

Medium-sized retailers in Latin America are transitioning from Generative AI (GenAI) experimentation to full-scale deployment, aiming to unify sales funnels through autonomous payment agents that deliver measurable operational impact across the digital ecosystem.

The implementation of these technologies addresses the urgent need to manage unstructured data and automate critical consumer touchpoints.

“The industry is moving toward a new sales channel in which agents that deeply understand the user manage payment credentials and purchase decisions,” says Rene Salazar, global partnerships, expansion, and incubation for Latin America, Stripe. “Agents can reason—though not think—enabling them to execute autonomous transactions through specific prompts.”

This development reshapes traditional interactions, shifting from simple query-and-response models to end-to-end purchase journeys autonomously managed by AI.

Market Context

The sector’s technological evolution is expected to generate a total financial impact of US$9.2 trillion in retail by 2029, according to IHL Group. While GenAI represented only 9% of the sector’s total impact in 2023, it is projected to account for 78% by 2029, equivalent to approximately US$4.4 trillion.

Currently, data from IDC Europe indicates that 40% of global retailers remain in the experimentation phase, while 21% are already investing in active implementations.

In Mexico, the ecosystem faces structural challenges driven by high mobile penetration and limited access to traditional banking services, creating both constraints and opportunities for digital innovation.

GenAI supports these companies by processing unstructured data sources—such as emails, images, and social media content—to enhance customer service. Organizations leverage these inputs to train models that guide users toward relevant solutions, effectively automating early-stage customer interactions and decision-making processes.

Technical Implementation and Data Interoperability 

The maturation of GenAI adoption remains uneven across business segments. Currently, the most quantifiable returns on investment are concentrated in product discovery and customer service optimization.

Alejandra Soberon, country manager at Mixpanel, emphasizes the importance of eliminating data silos to unlock organizational value.

“The competitive advantage lies in understanding how customers prefer to buy and delivering exactly what they need at the moment of intent,” says Soberon. “Processes that previously took days can now be completed in seconds, allowing teams to adapt strategies in real time during high-demand events.”

To achieve this level of responsiveness, organizations are prioritizing the creation of a “single source of truth”, integrating data from CRM systems, e-commerce platforms, and behavioral analytics. This consolidation is critical for enabling AI models to deliver context-aware recommendations based on sentiment and intent analysis, ultimately reducing cart abandonment—a key performance metric in regional e-commerce.

Cybersecurity and Consumer Trust in Emerging Markets

In markets with elevated fraud risk, transparency and data protection are central to building consumer trust.

Eduardo Hamid, head of e-commerce, Samsung Electronics, highlights the increasing complexity of the consumer journey.

“Today’s customer researches extensively before making a purchase,” says Hamid. “While AI simplifies this process by addressing technical questions, seamless integration between CRM systems and customer service channels is essential to ensure a secure and reliable experience.”

The protection of personal data remains aligned with international regulatory frameworks. Alexandre Bartra, general manager for North America, Etam, notes that the primary barriers are organizational rather than purely technical.

He emphasizes that companies face cultural transformation challenges, often requiring extended internal “evangelization” processes. “Management and IT teams must transition toward open data architectures that enable deep analysis without compromising privacy, in line with standards such as the General Data Protection Regulation (GDPR),” he adds.

Human Capital and Organizational Reskilling

The transition toward operational autonomy requires investment strategies that extend beyond technology deployment. A study by the IBM Institute for Business Value indicates that 41% of the retail workforce will require reskilling due to AI and automation.

As a result, leading organizations are shifting focus from external hiring to internal capability building, prioritizing digital skills, data governance, and phased implementation strategies.

This transformation enables retailers to scale dynamic pricing, predictive logistics, and real-time decision-making. David Jaime, regional account director for tech and durables in Latin America, NielsenIQ, notes that the success of GenAI ultimately depends on its ability to deliver measurable business outcomes.

“By optimizing these components, companies can secure a sustainable competitive advantage in an increasingly complex consumer environment,” says Jaime.

The integration of GenAI is no longer a forward-looking concept but an immediate operational imperative. Industry experts agree that retailers capable of bridging the gap between experimentation and production will be better positioned to capitalize on the accelerated growth of the digital economy in Mexico and across Latin America.