AI Personalization: The Key to Deeper Understanding of Customers

Generative artificial intelligence is ushering in a new era in e-commerce: the era of empathic hyper-personalization. By combining an "AI First" strategy with a "Humane First" approach, brands are creating more human shopping experiences without sacrificing efficiency or results.

It is becoming increasingly important for organizations in the digital ecosystem to recognize that AI has arrived not to replace humans, but to amplify the best of humanity — intuition, empathy, and ethics — and to understand the customer like never before.

We are living through a digital genesis, where the question is no longer what we can do with AI, but who we choose to be when we use it.

AI-driven personalization is no longer just about automation and scale, it is becoming a pact between technology and humanity. As I argue in the “Human Augmented AI Manifesto,” the formula is clear: Augmented Artificial Intelligence = AI First + Human First.

In other words, adopting AI means placing technology at the forefront, but without leaving humanity behind. This technology is not here to replace us, but to empower us. It must be as strategic as it is empathetic, as efficient as it is ethical, as predictive as it is human-centered.

This vision requires a rethinking of our principles. It’s no longer enough to declare ethical values. We must practice them. It means moving from declarative ethics to applied ethics, integrating responsibility and transparency into everything from algorithm design to organizational culture.

It means governing artificial intelligence through humanist principles: explainable algorithms, controlled biases, and respect for customers’ privacy and dignity in every interaction. After all, “the challenge is not for AI to become more human, but for us not to become less human.”

But for this humanist governance to be feasible and scalable, we must broaden the concept of governance beyond the ethical and cultural. It must also encompass the governance of the technological and data architectures that support AI in all its forms.

We cannot speak of responsible, efficient, and human-centered AI without first designing a composable and pragmatic infrastructure, one that coherently connects various AI initiatives (generative, predictive, analytical, or automated) across all applicable dimensions.

From the front end, with hyper-personalized consumer experiences, to the back end — in logistics, commerce, finance, operations, or HR — every implementation must be part of an interconnected ecosystem that avoids fragmentation.

One of the greatest current risks is falling into the proliferation of “AI silos,” where different departments develop disconnected solutions without a shared data framework, integration standards, or interoperability criteria.

This disconnection not only threatens operational efficiency, but also undermines AI’s core promise in digital commerce: to create continuous, coherent, and deeply relevant customer experiences.

Therefore, AI architecture must be both federated and orchestrated — designed with a customer-centric logic, but also with AI as the coordinating axis, enabling transversal capabilities. Only then can we build a true “augmented organizational brain,” with AI acting as a co-pilot — or even a pilot — at every customer touchpoint and every link in the value chain.

Maintaining this moral, procedural, and architectural compass is critical to ensuring that mass personalization doesn’t sacrifice empathy for the sake of efficiency or scalability. This also ensures that the approach is sustainable and capable of generating high, near-exponential impact, not just in the short term but in the medium term as well.

The good news is that this more humanized approach is already translating into concrete actions in the Latin American digital ecosystem. Some of the region’s leading companies are using generative AI to meaningfully improve user relationships.

For instance, e-commerce platforms like MercadoLibre have begun implementing models like GPT-3.5 and GPT-4 to automatically personalize product descriptions, adapting titles and details based on the country. This means a customer in Mexico or Argentina receives information tailored to their everyday language and cultural references, creating a much more relevant and relatable experience.

AI is also being used to send personalized push notifications based on each user’s individual interests and behaviors. This practice is showing significantly higher engagement levels compared to generic messaging.

Another innovative application is the real-time summarization of product reviews, allowing shoppers to quickly grasp the general sentiment about a product. These intelligent summaries are already driving visible improvements in conversion rates.

The use of AI across value chains is having a measurable impact. A recent analysis revealed that the implementation of smart recommendation engines can increase conversion rates by an average of 26% and boost average order value by 11%.

In fact, for some brands, personalized recommendations already account for 10% to 30% of total revenue. In one specific case, a leading sports retailer increased conversions by 5.2% and revenue by 10.7% after integrating AI-based product recommendations on its website. The lesson is clear: understanding the customer better pays off, both in immediate sales and long-term loyalty.

Consumers, for their part, are embracing these personalized experiences. According to Salesforce, around 73% of customers now expect some degree of personalization in their interactions with brands. Meanwhile, over a third of companies (37%) recognize that AI has improved their service personalization, creating more relevant experiences.

However, effective personalization requires a delicate touch. About 56% of consumers say their satisfaction “depends on how” AI is used. They appreciate helpful recommendations but reject invasive or impersonal ones. AI is a tool, not a substitute for empathy. Companies that strike the right balance between automation and human warmth will be the ones to reap the greatest rewards.

Ultimately, AI-driven personalization is emerging as the most promising path to a deep understanding of the customer and a richer shopping experience. But that path comes with the responsibility of putting people at the center of the strategy, guiding technology with a humanist purpose.

Latin American organizations must adopt this “AI First with Humane First” paradigm to build emotional connections with their customers. This is just as essential as having a solid sales strategy.

The provocative question we are left to reflect on is: Are we ready for AI to know each customer well enough to anticipate their needs without losing our human essence in the process?